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@Article{Arkinetal97,
author
= "A. Arkin and P. Shen and
J. Ross",
title
= "A Test Case of
Correlation Metric Construction of a Reaction Pathway from Measurements",
journal
= "Science",
volume
= "277",
number
= "5330",
pages
= "1275--1279",
year = "1997",
url = "http://www.sciencemag.org/cgi/reprint/277/5330/1275.pdf",
keywords
= "reconstruction, kinetic,
metabolism, analysis, multidimensional scaling, Correlation Metric Construction
",
abstract
= "A method for the prediction
of the interactions within complex reaction networks from experimentally
measured time series of the concentration of the species composing the system
has been tested experimentally on the first few steps of the glycolytic
pathway. The reconstituted reaction system, containing eight enzymes and 14
metabolic intermediates, was kept away from equilibrium in a continuous-flow,
stirred-tank reactor. Input concentrations of adenosine monophosphate and
citrate were externally varied over time, and their concentrations in the
reactor and the response of eight other species were measured. Multidimensional
scaling analysis and heuristic algorithms applied to two-species time-lagged
correlation functions derived from the time series yielded a diagram from which
the interactions among all of the species could be deduced. The diagram
predicts essential features of the known reaction network in regard to chemical
reactions and interactions among the measured species. The approach is
applicable to many complex reaction systems.",
crossref
= "",
}
@Article{Akutsuetal00,
author
= "T. Akutsu and S. Miyano
and S. Kuhara",
title
= "Algorithms for
Identifying Boolean Networks and Related Biological Networks Based on Matrix
Multiplication and Fingerprint Function.",
journal
= "Journal of Computational
Biology",
volume
= "7",
number
= "3",
pages
= "331--343",
year = "2000",
url = "http://tisbe.catchword.com/vl=60010963/cl=2/nw=1/rpsv/catchword/mal/10665277/v7n3/s2/p331",
keywords
= "Boolean network,
reconstruction, pathway discovery, qualitative, regulatory, analysis",
abstract
= "Due to the recent progress
of the DNA microarray technology, a large number of gene expression profile
data are being produced. How to analyze gene expression data is an important
topic in computational molecular biology. Several studies have been done using the
Boolean network as a model of a genetic network. This paper proposes efficient
algorithms for identifying Boolean networks of bounded indegree and related
biological networks, where identification of a Boolean network can be
formalized as a problem of identifying many Boolean functions simultaneously.
For the identification of a Boolean network, an O(mn(D)(+1)) time naive
algorithm and a simple O(mn(D)) time algorithm are known, where n denotes the
number of nodes, m denotes the number of examples, and D denotes the maximum
indegree. This paper presents an improved O(m(omega-2)n(D) + mn(D+omega-3))
time Monte-Carlo type randomized algorithm, where omega is the exponent of
matrix multiplication (currently, omega < 2.376). The algorithm is obtained
by combining fast matrix multiplication with the randomized fingerprint
function for string matching. Although the algorithm and its analysis are
simple, the result is nontrivial and the technique can be applied to several
related problems.",
crossref
= "PMID:11125433",
}
@Article{Akutsuetal00a,
author
= "T. Akutsu and S. Miyano
and S. Kuhara",
title
= "Inferring qualitative
relations in genetic networks and metabolic pathways",
journal
= "Bioinformatics",
volume
= "16",
number
= "8",
pages
= "727--734",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/8/727.pdf",
keywords
= "Boolean network,
reconstruction, pathway discovery, qualitative, metabolism, regulatory,
S-systems, stochastic, analysis",
abstract
= "Motivation: Inferring
genetic network architecture from time series data of gene expression patterns
is an important topic in bioinformatics. Although inference algorithms based on
the Boolean network were proposed, the Boolean network was not sufficient as a
model of a genetic network. Results: First, a Boolean network model with noise
is proposed, together with an inference algorithm for it. Next, a qualitative
network model is proposed, in which regulation rules are represented as
qualitative rules and embedded in the network structure. Algorithms are also
presented for inferring qualitative relations from time series data. Then, an
algorithm for inferring S-systems (synergistic and saturable systems) from time
series data is presented, where S-systems are based on a particular kind of
nonlinear differential equation and have been applied to the analysis of
various biological systems. Theoretical results are shown for Boolean networks
with noises and simple qualitative networks. Computational results are shown
for Boolean networks with noises and S-systems, where real data are not used
because the proposed models are still conceptual and the quantity and quality
of currently available data are not enough for the application of the proposed
methods.",
crossref
= "PMID:11099258",
}
@InProceedings{Akutsuetal98,
author
= "T. Akutsu and S. Kuhara
and O. Maruyama and S. Miyano",
title
= "A System for Identifying
Genetic Networks from Gene Expression Patterns Produced by Gene Disruptions and
Overexpressions",
booktitle = "Genome Informatics",
volume
= "9",
pages
= "151--160",
year = "1998",
editor
= "K. Asai and S. Miyano and
T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.jsbi.org/journal/GIW98/GIW98F16.pdf",
keywords
= "Boolean network,
asynchronous, reconstruction, regulatory, mutation, simulation, visualization,
analysis",
abstract
= "A hot research topic in
genomics is to analyze the interactions between genes by systematic gene
disruptions and gene overexpressions. Based on a boolean network model without
time delay, we have been investigating efficient strategies for identifying a
genetic network by multiple gene disruptions and overexpressions. This paper
first shows the relationship between our boolean network model without time
delay and the standard synchronous boolean network model. Then we present a
simulator of boolean networks without time delay for multiple gene disruptions
and gene overexpressions, which includes a genetic network identifier with a
graphic interface that generates instructions for experiments of gene
disruptions and overexpressions.",
crossref
= "PMID:11072331",
}
@InProceedings{Akutsuetal00b,
author
= "T. Akutsu and S. Miyano
and S. Kuhara",
title
= "Algorithms for inferring
qualitative models of biological networks",
booktitle
= "Pacific Symposium on Biocomputing",
volume
= "5",
pages
= "293--304",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/akutsu.pdf",
keywords
= "Boolean network,
qualitative, reconstruction, regulatory, biochemistry, S-systems, kinetic, metabolism",
abstract
= "Modeling genetic networks
and metabolic networks is an important topic in bioinformatics. We propose a
qualitative network model which is a combination of the Boolean network and
qualitative reasoning, where qualitative reasoning is a kind of reasoning
method well-studied in Artificial Intelligence. We also present algorithms for
inferring qualitative networks from time series data and an algorithm for
inferring S-systems (synergistic and saturable systems) from time series data,
where S-systems are based on a particular kind of nonlinear differential
equation and have been applied to the analysis of various biological
systems.",
crossref
= "PMID:10902178",
}
@InProceedings{Akutsuetal99,
author
= "T. Akutsu and S. Miyano
and S. Kuhara",
title
= "Identification of genetic
networks from a small number of gene expression patterns under the Boolean
network model",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "17--28",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Akutsu.pdf",
keywords
= "Boolean network,
qualitative, reconstruction",
abstract
= "Liang, Fuhrman and Somogyi
(PSB98, 18-29, 1998) have described an algorithm for inferring genetic network
architectures from state transition tables which correspond to time series of
gene expression patterns, using the Boolean network model. Their results of
computational experiments suggested that a small number of state transition
(INPUT/OUTPUT) pairs are sufficient in order to infer the original Boolean
network correctly. This paper gives a mathematical proof for their observation.
Precisely, this paper devises a much simpler algorithm for the same problem and
proves that, if the indegree of each node (i.e., the number of input nodes to
each node) is bounded by a constant, only O(log n) state transition pairs (from
2n pairs) are necessary and sufficient to identify the original Boolean network
of n nodes correctly with high probability. We made computational experiments
in order to expose the constant factor involved in O(log n) notation. The
computational results show that the Boolean network of size 100,000 can be
identified by our algorithm from about 100 INPUT/OUTPUT pairs if the maximum
indegree is bounded by 2. It is also a merit of our algorithm that the
algorithm is conceptually so simple that it is extensible for more realistic
network models.",
crossref
= "PMID:10380182",
}
@Article{AlvesandSavageau00a,
author
= "R. Alves and M. A.
Savageau",
title
= "Extending the method of
mathematically controlled comparison to include numerical comparisons",
journal
= "Bioinformatics",
volume
= "16",
number
= "9",
pages
= "786--798",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/9/786.pdf",
keywords
= "kinetic, power-law
formalism, mathematically controlled comparison, numerical, quantitative,
qualitative, analysis, systemic, comparative, metabolism, regulatory, immune,
statistical, biochemistry",
abstract = "Motivation: The method of mathematically controlled comparison has been used for some time to determine which of two alternative regulatory designs is better according to specific quantitative criteria for functional effectiveness. In some cases, the results obtained using this technique are general and independent of parameter values and the answers are clear-cut. In others, the result might be general, but the demonstration is difficult and numerical results with specific parameter values can help to clarify the situation. In either case, numerical results with specific parameter values can also provide an answer to the question of how much larger the values might be. In contrast, a more ambiguous result is obtained when either of the alternatives can have the larger value for a given systemic property, depending on the specific values of the parameters. In any case, introduction of specific values for the parameters reduces the generality of the results. Therefore, we have been motivated to develop and apply statistical methods that would permit the use of numerical values for the parameters and yet retain some of the generality that makes mathematically controlled comparison so attractive. Results: We illustrate this new numerical method in a step-by-step application using a very simple didactic example. We also validate the results by comparison with the corresponding results obtained using the previously developed analytical method. The analytical approach is briefly present for reference purposes, since some of the same key concepts are needed to understand the numerical method and the results are needed for comparison. The numerical method confirms the qualitative differences between the systemic behavior of alternative designs obtained from the analytical method. In addition, the numerical method allows for quantification of the differences and it provides results that are general in a statistical sense. For example, the older analytical method showed that overall feedback inhibition in an unbranched pathway makes the system more robust whereas it decreases the stability margin of the steady state. The numerical method shows that the magnitudes of these differences are not comparable. The differences in stability margins (1-2% on average) are small when compared to the differences in robustness (50-100% on average). Furthermore, the numerical method shows that the system with overall feedback responds more quickly to change than the otherwise equivalent system without overall feedback. These results suggest reasons why overall feedback inhibition is such a prevalent regulatory pattern in unbranched biosynthetic pathways.",
crossref
= "PMID:11108701",
}
@Article{AlvesandSavageau00b,
author
= "R. Alves and M. A.
Savageau",
title
= "Systemic properties of
ensembles of metabolic networks: application of graphical and statistical
methods to simple unbranched pathways",
journal
= "Bioinformatics",
volume
= "16",
number
= "9",
pages
= "534--547",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/6/534.pdf",
keywords
= "kinetic, power-law
formalism, mathematically controlled comparison, numerical, quantitative,
qualitative, analysis, systemic, comparative, metabolism, regulatory, immune,
statistical, pathway classification, biochemistry, structural class, behavioral
class",
abstract
= "Motivation: Mathematical
models are the only realistic method for representing the integrated dynamic
behavior of complex biochemical networks. However, it is difficult to obtain a
consistent set of values for the parameters that characterize such a model.
Even when a set of parameter values exists, the accuracy of the individual
values is questionable. Therefore, we were motivated to explore statistical
techniques for analyzing the properties of a given model when knowledge of the
actual parameter values is lacking. Results: The graphical and statistical
methods presented in the previous paper are applied here to simple unbranched
biosynthetic pathways subject to control by feedback inhibition. We represent
these pathways within a canonical nonlinear formalism that provides a regular
structure that is convenient for randomly sampling the parameter space. After
constructing a large ensemble of randomly generated sets of parameter values,
the structural and behavioral properties of the model with these parameter sets
are examined statistically and classified. The results of our analysis
demonstrate that certain properties of these systems are strongly correlated,
thereby revealing aspects of organization that are highly probable independent
of selection. Finally, we show how specification of a given behavior affects
the distribution of acceptable parameter values.",
crossref
= "PMID:10980151",
}
@Article{AlvesandSavageau00c,
author
= "R. Alves and M. A.
Savageau",
title
= "Comparing systemic properties of ensembles of biological
networks by graphical and statistical methods.",
journal
= "Bioinformatics",
volume
= "16",
number
= "9",
pages
= "527--533",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/6/527.pdf",
keywords
= "kinetic, power-law
formalism, mathematically controlled comparison, numerical, quantitative,
qualitative, analysis, systemic, comparative, metabolism, regulatory, immune,
statistical, classification, biochemistry, graphical",
abstract
= "Motivation: When dealing with
questions that concern a general class of models for biological networks, large
numbers of distinct models within the class can be grouped into an ensemble
that gives a statistical view of the properties for the general class.
Comparing properties of different ensembles through the use of point measures
(e.g. medians, standard deviations, correlation coefficients) can mask
inhomogeneities in the correlations between properties. We are therefore
motivated to develop strategies that allow these inhomogeneities to be more
easily detected. Results: Methods are described for constructing ensembles of
models within the context of a Mathematically Controlled Comparison. A Density
of Ratios Plot for a given systemic property is then defined as follows: the y axis
represents the value of the systemic property in a reference model divided by
the value in the alternative model, and the x axis represents the value of the
systemic property in the reference model. Techniques involving moving quantiles
are introduced to generate secondary plots in which correlations and
inhomogeneities in correlations are more easily detected. Several examples that
illustrate the advantages of these techniques are presented and
discussed.",
crossref
= "PMID:10980150",
}
@Article{AshthagiriandLauffenburger00,
author
= "A. R. Asthagiri and D. A.
Lauffenburger",
title
= "Bioengineering models of
cell signaling",
journal
= "Annual Review of Biomedical
Engineering",
volume
= "2",
number
= "",
pages
= "31--53",
year = "2000",
url = "http://bioeng.annualreviews.org/cgi/reprint/2/1/31",
keywords
= "analysis, kinetic,
biochemical, signaling, modular, engineering",
abstract
= "Strategies for rationally
manipulating cell behavior in cell-based technologies and molecular
therapeutics and understanding effects of environmental agents on physiological
systems may be derived from a mechanistic understanding of underlying signaling
mechanisms that regulate cell functions. Three crucial attributes of signal
transduction necessitate modeling approaches for analyzing these systems: an
ever-expanding plethora of signaling molecules and interactions, a highly
interconnected biochemical scheme, and concurrent biophysical regulation.
Because signal flow is tightly regulated with positive and negative feedbacks
and is bidirectional with commands traveling both from outside-in and
inside-out, dynamic models that couple biophysical and biochemical elements are
required to consider information processing both during transient and
steady-state conditions. Unique mathematical frameworks will be needed to
obtain an integrated perspective on these complex systems, which operate over
wide length and time scales. These may involve a two-level hierarchical
approach wherein the overall signaling network is modeled in terms of effective
"circuit" or "algorithm" modules, and then each module is
correspondingly modeled with more detailed incorporation of its actual
underlying biochemical/biophysical molecular interactions.",
}
@Article{Arkinetal98,
author
= "A. Arkin and J. Ross and
H.H. McAdams",
title
= "Stochastic kinetic
analysis of developmental pathway bifurcation in phage lambda-infected
Escherichia coli cells",
journal
= "Genetics",
volume
= "149",
number
= "",
pages
= "1633--1648",
year = "1998",
url = "http://www.genetics.org/cgi/reprint/149/4/1633.pdf",
keywords
= "kinetic, biochemical,
signaling, regulatory, stochastic, simulation",
abstract = "Fluctuations in rates of gene
expression can produce highly erratic time patterns of protein production in
individual cells and wide diversity in instantaneous protein concentrations
across cell populations. When two independently produced regulatory proteins
acting at low cellular concentrations competitively control a switch point in a
pathway, stochastic variations in their concentrations can produce
probabilistic pathway selection, so that an initially homogeneous cell
population partitions into distinct phenotypic subpopulations. Many pathogenic
organisms, for example, use this mechanism to randomly switch surface features
to evade host responses. This coupling between molecular-level fluctuations and
macroscopic phenotype selection is analyzed using the phage lambda
lysis-lysogeny decision circuit as a model system. The fraction of infected
cells selecting the lysogenic pathway at different phage:cell ratios, predicted
using a molecular-level stochastic kinetic model of the genetic regulatory circuit,
is consistent with experimental observations. The kinetic model of the decision
circuit uses the stochastic formulation of chemical kinetics, stochastic
mechanisms of gene expression, and a statistical-thermodynamic model of
promoter regulation. Conventional deterministic kinetics cannot be used to
predict statistics of regulatory systems that produce probabilistic outcomes.
Rather, a stochastic kinetic analysis must be used to predict statistics of
regulatory outcomes for such stochastically regulated systems.",
crossref = "PMID:9691025",
}
@Article{Ashburneretal00,
author
= "M. Ashburner and C. A.
Ball and J. A. Blake and D. Botstein and H. Butler and J. M. Cherry JM and A.
P. Davis and K. Dolinski and S. S. Dwight and J. T. Eppig and M. A. Harris and
D. P. Hill and L. Issel-Tarver and A. Kasarskis and S. Lewis and J. C. Matese
and J. E. Richardson and M. Ringwald and G. M. Rubin and G. Sherlock",
title
= "Gene ontology: tool for the
unification of biology. The Gene Ontology Consortium",
journal
= "Nature Genetics",
year = "2000",
volume
= "25",
number
= "1",
pages
= "25--29",
url = "http://www.nature.com/cgi-taf/DynaPage.taf?file=/ng/journal/v25/n1/full/ng0500_25.html",
keywords
= "ontology, knowledge
representation, database, implementation, GeneOntology, metabolism, signaling,
regulatory, compartment",
abstract
= "",
crossref = "PMID:10802651",
}
B
@Article{Bugrim01,
author
= "A. E. Bugrim",
title = "Logic-based approach to the analysis of spatially distributed biochemical networks ",
journal
= "",
volume
= "",
number
= "",
pages
= "",
year = "2001",
url = "",
note = "Submitted",
keywords
= "logic, spatial, analysis, simulation, reconstruction,
signaling, implementation",
abstract = "Recent studies show that spatial and temporal organization of intracellular processes plays a crucial role in signal transduction and cell metabolism. However, this kind of information is difficult to represent in databases and, therefore, is not easily available for large-scale data integration. In this paper I suggest a novel approach that allows, within a single computational framework, both storage and analysis of information on spatially distributed signaling and metabolic networks. Proposed method contains following major components: simplified representation of topology and geometry of the intracellular space, representation of biological molecules, their properties, sub-cellular localization, and interactions among them; and finally, a collection of algorithms for integrating these data, reconstructing biochemical networks, and predicting their dynamic behavior. This approach is illustrated by modeling a small signaling network.",
crossref
= "",
}
@Article{BeckerandRojas01,
author
= "M. Y. Becker and I.
Rojas",
title = "A graph layout algorithm for drawing metabolic pathways",
journal = "Bioinformatics",
volume
= "17",
number
= "5",
pages
= "461--467",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/5/461.pdf",
keywords
= "metabolism, visualization,
graph",
abstract
= "MOTIVATION: A large amount
of data on metabolic pathways is available in databases. The ability to
visualise the complex data dynamically would be useful for building more
powerful research tools to access the databases. Metabolic pathways are
typically modelled as graphs in which nodes represent chemical compounds, and
edges represent chemical reactions between compounds. Thus, the problem of
visualising pathways can be formulated as a graph layout problem. Currently
available visual interfaces to biochemical databases either use static images
or cannot cope well with more complex, non-standard pathways. RESULTS: This
paper presents a new algorithm for drawing pathways which uses a combination of
circular, hierarchic and force-directed graph layout algorithms to compute
positions of the graph elements representing main compounds and reactions. The
algorithm is particularly designed for cyclic or partially cyclic pathways or
for combinations of complex pathways. It has been tested on five sample
pathways with promising results.",
crossref
= "PMID:11331241",
}
@Unpublished{Boehringer00,
author = "",
title = "Boehringer Mannheim biochemical pathway chart",
year = "2000",
url = "http://www.expasy.ch/cgi-bin/search-biochem-index",
keywords
= "graphical, visualization,
signaling, metabolism, database, regulatory, Boehringer ",
abstract
= "A digitized version of our
Biochemical Pathway Chart is available on the ExPASy Molecular Biology Server
of the Geneva University Hospital and the University of Geneva. An electronic
index allows for the quick localization of any metabolite or enzyme on the
chart. In addition most enzyme names on the chart act as links to the extensive
ENZYME database.",
crossref
= "",
}
@Article{BecskeiandSerrano00,
author
= "A. Becskei and L.
Serrano",
title = "Engineering stability in gene networks by
autoregulation",
journal
= "Nature",
volume
= "405",
number
= "6786",
pages
= "590--593",
year = "2000",
keywords
= "engineering, feedback,
regulatory",
abstract
= "The genetic and biochemical
networks which underlie such things as homeostasis in metabolism and the
developmental programs of living cells, must withstand considerable variations
and random perturbations of biochemical parameters. These occur as transient
changes in, for example, transcription, translation, and RNA and protein
degradation. The intensity and duration of these perturbations differ between
cells in a population. The unique state of cells, and thus the diversity in a
population, is owing to the different environmental stimuli the individual
cells experience and the inherent stochastic nature of biochemical processes
(for example, refs 5 and 6). It has been proposed, but not demonstrated, that
autoregulatory, negative feedback loops in gene circuits provide stability,
thereby limiting the range over which the concentrations of network components
fluctuate. Here we have designed and constructed simple gene circuits
consisting of a regulator and transcriptional repressor modules in Escherichia
coli and we show the gain of stability produced by negative feedback.",
crossref
= "PMID:10850721",
}
@Article{Baderetal01,
author = "G. D. Bader and I. Donaldson and C. Wolting and B. F. Ouellette and T. Pawson and C. W. Hogue",
title = "BIND-The Biomolecular Interaction Network
Database",
journal
= "Nucleic Acids
Research",
volume
= "29",
number
= "1",
pages
= "242--245",
year = "2001",
url = "http://nar.oupjournals.org/cgi/reprint/29/1/242.pdf",
keywords
= "BIND, protein-protein,
database, complex, biochemistry, regulatory, signaling, conformation, graph,
kinetic, simulation, comparative, analysis, implementation, visualization,
ASN.1, exchange, markup",
abstract
= "The Biomolecular Interaction
Network Database (BIND; http://binddb.org) is a database designed to store full
descriptions of interactions, molecular complexes and pathways. Development of
the BIND 2.0 data model has led to the incorporation of virtually all
components of molecular mechanisms including interactions between any two
molecules composed of proteins, nucleic acids and small molecules. Chemical
reactions, photochemical activation and conformational changes can also be
described. Everything from small molecule biochemistry to signal transduction
is abstracted in such a way that graph theory methods may be applied for data
mining. The database can be used to study networks of interactions, to map
pathways across taxonomic branches and to generate information for kinetic
simulations. BIND anticipates the coming large influx of interaction
information from high-throughput proteomics efforts including detailed
information about post-translational modifications from mass spectrometry.
Version 2.0 of the BIND data model is discussed as well as implementation,
content and the open nature of the BIND project. The BIND data specification is
available as ASN.1 and XML DTD.",
crossref
= "PMID:11125103",
}
@Article{BaderandHogue00,
author
= "G. D. Bader and C. W.
Hogue",
title = "BIND--a data specification for storing and describing
biomolecular interactions",
journal
= "Bioinformatics",
volume
= "16",
number
= "5",
pages
= "465--477",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/5/465.pdf",
keywords
= "BIND, protein-protein,
database, complex, biochemistry, regulatory, signaling, conformation, graph,
kinetic, simulation, comparative, analysis, implementation, visualization,
ASN.1, exchange, markup, ontology, compartment, kinetic",
abstract
= "MOTIVATION: Proteomics is
gearing up towards high-throughput methods for identifying and characterizing
all of the proteins, protein domains and protein interactions in a cell and
will eventually create more recorded biological information than the Human
Genome Project. Each protein expressed in a cell can interact with various other
proteins and molecules in the course of its function. A standard data
specification is required that can describe and store this information in all
its detail and allow efficient cross-platform transfer of data. A complete
specification must be the basis for any database or tool for managing and
analysing this information. RESULTS: We have defined a complete data
specification in ASN.1 that can describe information about biomolecular
interactions, complexes and pathways. Our group is using this data specification
in our database, the Biomolecular Interaction Network Database (BIND). An
interaction record is based on the interaction between two objects. An object
can be a protein, DNA, RNA, ligand, molecular complex or an interaction.
Interaction description encompasses cellular location, experimental conditions
used to observe the interaction, conserved sequence, molecular location,
chemical action, kinetics, thermodynamics, and chemical state. Molecular
complexes are defined as collections of more than two interactions that form a
complex, with extra descriptive information such as complex topology. Pathways
are defined as collections of more than two interactions that form a pathway,
with additional descriptive information such as cell cycle stage. A request for
proposal of a human readable flat-file format that mirrors the BIND data
specification is also tendered for interested parties. AVAILABILITY: The ASN.1
data specification for biomolecular interaction, molecular complex and pathway
data is available at ftp://bioinfo.mshri.on.ca/pub/BIND/Spec/bind.asn. An
interactive browser for this document is available through our homepage at
http://bioinfo.mshri.on.ca/BIND/asn-browser/",
crossref
= "PMID:10871269",
}
@Article{Bentolila96,
author
= "S. Bentolila",
title = "A grammar describing 'biological binding operators'
to model gene regulation",
journal
= "Biochimie",
volume
= "78",
number
= "5",
pages
= "335--350",
year = "1996",
url = "",
keywords
= "grammar, regulatory,
knowledge representation, biochemistry, signaling, protein-protein,
implementation, simulation, combinatorial, quantitative",
abstract
= "The study of the mechanisms
involved in the regulation of protein synthesis has become sufficiently
advanced that it is appropriate to think about a knowledge formalism. The
objective of the syntactic grammar which we present in this article is a
representation of these phenomena which take place in the context of the cell.
The proposed model considers two types of objects: transcriptional units on DNA
and regulatory or structural proteins which are synthesized, and which are, in
the case of regulatory proteins, themselves destined to activate or repress
other transcriptional units in a later phase. A transcriptional unit is
described by the list of its active sites (operator, promoter, binding sites
for transcription factors). A regulatory protein is described by the list of
its active sites (binding domain, activation domain, binding domain for
ligand). The DNA sites and the protein domains are the terminal symbols of the
proposed grammar. The interaction of these proteins with the DNA, and in
certain cases preliminary interactions between proteins, leads to one of two
antagonistic actions: expression or repression of the transcriptional unit.
These protein-protein and protein-DNA interactions are grouped into syntactic
categories (induction, inhibition, initiation complex, repressor complex,
activation complex) which are called biological binding operators. The
expression/repression action are described by grammar rules which provide the
chain of execution by biological binding operators for the four
activable/repressible regulatory systems modulated by positive/negative
co-factors. The object of this modelization is the observation of a cell in a
given state for a given process which involves a cascade of genes. This grammar
is implemented by a simulation program which allows the user to vary the
initial state of the cell and also to change parameters related to time and
quantity. This syntactic and generative grammar is independent of the
specificity of each transcriptional unit. The simulation uses examples which
may combine several regulatory systems: the lac operon, regulation of
metallothionein, galactose catabolism in yeast, the tryptophan operon, and
phage lysogenic/lytic cascades.",
crossref
= "PMID:8905153",
}
@InProceedings{Blaschkeetal99,
author
= "C. Blaschke and M. A.
Andrade and C. Ouzounis and A. Valencia",
title
= "Automatic extraction of
biological information from scientific text: protein-protein
interactions",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "7",
pages
= "60--67",
year = "1999",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "http://montblanc.cnb.uam.es/medline_interactions/CBlaschke99.pdf",
keywords
= "implementation, literature,
NLP, biochemistry, protein-protein, information extraction,
reconstruction",
abstract
= "We describe the basic design
of a system for automatic detection of protein-protein interactions extracted
from scientific abstracts. By restricting the problem domain and imposing a
number of strong assumptions which include pre-specified protein names and a limited
set of verbs that represent actions, we show that it is possible to perform
accurate information extraction. The performance of the system is evaluated
with different cases of real-world interaction networks, including the
Drosophila cell cycle control. The results obtained computationally are in good
agreement with current biological knowledge and demonstrate the feasibility of
developing a fully automated system able to describe networks of protein
interactions with sufficient accuracy.",
crossref
= "PMID:10786287",
}
@Article{Bergeronetal98,
author
= "A. Bergeron and P. Geanta1and
D. Bergeron",
title
= "The Death Factors: a
Combinatorial Analysis",
journal
= "In Silico Biology",
year = "1998",
volume
= "1",
number
= "",
pages
= "",
url = "http://www.bioinfo.de/isb/1998/01/0013/",
keywords
= "combinatorial,
protein-protein, implementation, simulation, stochastic, Virtual
Laboratory",
abstract
= "This paper presents
theoretical and computational tools to understand how a small group of
proteins, the death factors, are involved in widely different behavior of the
cell. Experiments were done using a virtual laboratory that can simulate
cellular response to different external stimuli. WARNING: It is not certain
which of the theoretical protein clusters described here really occur in
nature. In addition, the rules of cluster assembly are combinatorial, and thus
an oversimplification to describe the real situation.",
crossref = "",
}
@InProceedings{Bergeronetal97,
author
= "A. Bergeron and E. Gaul
and D. Bergeron",
title
= "Combinatorial tools for the analysis of transcriptional
regulation",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "2",
pages
= "62--73",
year = "1997",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www-smi.stanford.edu/people/altman/psb97/bergeron.pdf",
keywords
= "simulation, signaling,
regulatory, protein-protein, combinatorial, implementation, Virtual Laboratory,
stochastic",
abstract
= "In this paper, we discuss
virtual experiments for the study of major regulatory processes such as translation,
signalization or transcription pathways. An essential part of these processes
is the formation of protein clusters held together by a small number of binding
domains that can be shared by many different proteins. Analysis of these
clusters is complicated by the vast number of different arrangements of
proteins that can trigger a specific reaction. We propose combinatorial tools
that can help predict the effects on the rate of transcription of either
changes in transcriptional factors concentration, or due to the introduction of
chimeras combining domains not usually present on a protein.",
crossref
= "PMID:9390280",
}
@Article{Bodnar97,
author
= "J. W. Bodnar",
title
= "Programming the Drosophila
embryo",
journal
= "Journal of Theoretical
Biology",
volume
= "188",
number
= "4",
pages
= "391--445",
year = "1997",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1996.0328/pdf",
keywords
= "implementation, Boolean
logic, spatial, analysis, regulatory, hierarchical",
abstract
= "A critical step in
understanding the mechanisms of development is in defining the steps at the
molecular, cellular, and organismal levels in the developmental program for a
given organism-so that given the egg one can predict not only how the embryo
will develop but also how that embryo evolved from its ancestors. Using methods
employed by chemists and engineers in modeling hierarchical systems, I have
integrated current theory and experiment into a calculational method that can
model early Drosophila embryogenesis on a personal computer. This quantitative
calculation tool is simple enough to be useful for experimentalists in
designing experiments yet detailed enough for theoreticians to derive new
insights on the evolution of developmental genetic networks. By integrating the
strengths of theoretical and experimental methods into a single engineering
model that can compute the cascade of genetic networks in a real organism, I
provide a new calculational tool that can apply current theory to current
experimental data to study the evolution of developmental programs.",
crossref
= "PMID:9367733",
}
@Article{Burstein95,
author
= "Z. Burstein",
title
= "A network model of
developmental gene hierarchy",
journal
= "Journal of Theoretical
Biology",
volume = "174",
number
= "1",
pages
= "1--11",
year = "1995",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1995.0075/pdf",
keywords
= "spatial, hierarchical,
neural network, simulation, regulatory",
abstract
= "A network model of
development governing the whole temporal and spatial hierarchy of early
embryogenesis and pattern formation in Drosophila is introduced. The network is
related to a neural network model, with its units being developmental genes
mostly connected by the genes' DNA-binding products. The developmental
network's agreement with predictions regarding architecture and function of the
neural network provides adequate grounds for an analogy between the two. The
model is tested through computer simulations—predictions compare favorably with
experimental observations. The model not only incorporates a program of control
at gene level, but also makes a direct connection with current molecular
studies throughout the whole hierarchy of the early embryogenesis of
Drosophila.",
crossref
= "PMID:7643603",
}
@Article{Bray95,
author
= "D. Bray",
title
= "Protein molecules as
computational elements in living cells",
journal
= "Nature",
volume
= "376",
number
= "6538",
pages
= "307--312",
year = "1995",
url = "",
keywords
= "signaling, PDP network, neural
network",
abstract
= "Many proteins in living
cells appear to have as their primary function the transfer and processing of
information, rather than the chemical transformation of metabolic intermediates
or the building of cellular structures. Such proteins are functionally linked
through allosteric or other mechanisms into biochemical 'circuits' that perform
a variety of simple computational tasks including amplification, integration
and information storage.",
crossref
= "PMID:7630396",
}
@Article{Bray90,
author
= "D. Bray",
title
= "Intracellular signalling
as a parallel distributed process",
journal
= "Journal of Theoretical
Biology",
volume
= "143",
number
= "2",
pages
= "215--231",
year = "1990",
url = "",
keywords
= "signaling, PDP network,
neural network",
abstract
= "Living cells respond to
their environment by means of an interconnected network of receptors, second
messengers, protein kinases and other signalling molecules. This article
suggests that the performance of cell signalling pathways taken as a whole has
similarities to that of the parallel distributed process networks (PDP
networks) used in computer-based pattern recognition. Using the response of
hepatocytes to glucagon as an example, a procedure is described by which a PDP
network could simulate a cell signalling pathway. This procedure involves the
following steps: (a) a bounded set of molecules is defined that carry the
signals of interest; (b) each of these molecules is represented by a PDP-type
of unit, with input and output functions and connection weights corresponding
to specific biochemical parameters; (c) a "learning algorithm" is
applied in which small random changes are made in the parameters of the cell
signalling units and the new network is then tested by a selection procedure in
favour of a specific input-output relationship. The analogy with PDP networks
shows how living cells can recognize combinations of environmental influences,
how cell responses can be stabilized and made resistant to damage, and how
novel cell signaling pathways might appear during evolution.",
crossref
= "PMID:2385105",
}
@Article{BrayandLay97,
author
= "D. Bray and S. Lay",
title
= "Computer-based analysis
of the binding steps in protein complex formation",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "94",
number
= "25",
pages
= "13493--13498",
year = "2000",
url = "http://www.pubmedcentral.nih.gov/picrender.cgi?artid=14291&pictype=5",
keywords
= "kinetic, spatial, analysis,
signaling, biochemistry, complex, implementation, StochSim",
abstract
= "Computer models were used to
examine whether and under what conditions the multimeric protein complex is
inhibited by high concentrations of one of its components-an effect analogous
to the prozone phenomenon in precipitin tests. A series of idealized simple
"ball-and-stick" structures representing small oligomeric complexes
of protein molecules formed by reversible binding reactions were analyzed to
determine the binding steps leading to each structure. The equilibrium state of
each system was then determined over a range of starting concentrations and Kds
and the steady-state concentration of structurally complete oligomer calculated
for each situation. A strong inhibitory effect at high concentrations was shown
by any protein molecule forming a bridge between two or more separable parts of
the complex. By contrast, proteins linked to the outside of the complex by a
single bond showed no inhibition whatsoever at any concentration. Nonbridging,
multivalent proteins in the body of the complex could show an inhibitory effect
or not depending on the structure of the complex and the strength of its bonds.
On the basis of this study, we suggest that the prozone phenomenon will occur
widely in living cells and that it could be a crucial factor in the regulation
of protein complex formation.",
crossref
= "PMID:9391053",
}
@Article{Brownetal96,
author
= "G. C. Brown and H. V.
Westerhoff and B. N. Kholodenko",
title
= "Molecular control
analysis: control within proteins and molecular processes",
journal
= "Journal of Theoretical
Biology",
volume
= "182",
number
= "3",
pages
= "389--396",
year = "1996",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1996.0178/pdf",
keywords
= "kinetic, analysis, molecular
control, metabolism, signaling, steady state",
abstract
= "Molecular control analysis
is a method for analysing the extent to which the different elementary steps or
rate constants within a molecular process limit the steady-state rate (or other
variables) of that process. Any process which may be described by a kinetic
diagram of transitions between states of the system may be analysed by
molecular control analysis, and this approach has previously been used to
analyse control within enzymes, transporters, enzyme complexes, channelled
pathways, and group-transfer pathways. We outline the theory of molecular
control analysis here, and illustrate its use by analysing control within
enzymes (three beta-lactamases). Further potential applications include
signal-transduction processes, protein folding, and chemical reactions.",
crossref
= "PMID:8944172",
}
@Article{Brayetal98,
author
= "D. Bray and M. D. Levin
and C. J. Morton-Firth",
title
= "Receptor clustering as a
cellular mechanism to control sensitivity",
journal
= "Nature",
volume
= "393",
number
= "6680",
pages
= "85--88",
year = "1998",
keywords
= "kinetic, spatial, analysis,
signaling, biochemistry",
abstract
= "Chemotactic bacteria such as
Escherichia coli can detect and respond to extremely low concentrations of
attractants, concentrations of less than 5 nM in the case of aspartate. They
also sense gradients of attractants extending over five orders of magnitude in
concentration (up to 1 mM aspartate). Here we consider the possibility that
this combination of sensitivity and range of response depends on the clustering
of chemotactic receptors on the surface of the bacterium. We examine what will
happen if ligand binding changes the activity of a receptor, propagating this
change in activity to neighbouring receptors in a cluster. Calculations based
on these assumptions show that sensitivity to extracellular ligands increases
with the extent of spread of activity through an array of receptors, but that
the range of concentrations over which the array works is severely diminished.
However, a combination of low threshold of response and wide dynamic range can
be attained if the cell has both clusters and single receptors on its surface,
particularly if the extent of activity spread can adapt to external conditions.
A mechanism of this kind can account quantitatively for the sensitivity and
response range of E. coli to aspartate.",
crossref
= "PMID:9590695",
}
@Article{BrayandMortonFirth98,
author
= "D. Bray and M. D. Levin
and C. J. Morton-Firth",
title
= "Predicting temporal
fluctuations in an intracellular signalling pathway.",
journal
= "Journal of Theoretical
Biology",
volume
= "192",
number
= "1",
pages
= "117--128",
year = "1998",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1997.0651/pdf",
keywords
= "kinetic, stochastic,
temporal, signaling, biochemistry, simulation, implementation,
object-oriented",
abstract
= "We used a newly developed
stochastic-based program to predict the fluctuations in numbers of molecules in
a chemotactic signalling pathway of coliform bacteria. Specifically, we
examined temporal changes in molecules of CheYp, a cytoplasmic protein known to
influence the direction of rotation of the flagellar motor. Signalling
molecules in the vicinity of a flagellar motor were represented as individual
software objects interacting according to probabilities derived from
experimentally-observed concentrations and rate constants. The simulated CheYp
molecules were found to undergo random fluctuations in number about an average
corresponding to the deterministically calculated concentration. Both the
relative amplitude of the fluctuations, as a proportion of the total number of
molecules, and their average duration, increased as the simulated volume was
reduced. In a simulation corresponding to 10% of the volume of a bacterium, the
average duration of fluctuations was found to be 80.7 ms, which is much shorter
than the observed alternations between clockwise and counter-clockwise
rotations of tethered bacteria (typically 2.6 s). Our results are therefore not
in agreement with a simple threshold-crossing model for motor switching.
However, it is possible to filter the CheYp fluctuations to produce temporal
distributions closer to the observed swimming behaviour and we discuss the
possible implications for the control of motor rotation.",
crossref
= "PMID:9628844",
}
@Article{BhallaandIyengar99,
author
= "U. S. Bhalla and R.
Iyengar",
title
= "Emergent properties of
networks of biological signaling pathways",
journal
= "Science",
volume
= "283",
number
= "5400",
pages
= "381--387",
year = "1999",
url = "http://www.sciencemag.org/cgi/reprint/283/5400/381.pdf",
keywords
= "analysis, kinetic,
signaling, feedback, simulation, implementation, Kinetikit, GENESIS,
visualization",
abstract
= "Many distinct signaling
pathways allow the cell to receive, process, and respond to information. Often,
components of different pathways interact, resulting in signaling networks.
Biochemical signaling networks were constructed with experimentally obtained
constants and analyzed by computational methods to understand their role in
complex biological processes. These networks exhibit emergent properties such
as integration of signals across multiple time scales, generation of distinct
outputs depending on input strength and duration, and self-sustaining feedback
loops. Feedback can result in bistable behavior with discrete steady-state
activities, well-defined input thresholds for transition between states and
prolonged signal output, and signal modulation in response to transient
stimuli. These properties of signaling networks raise the possibility that
information for "learned behavior" of biological systems may be
stored within intracellular biochemical reactions that comprise signaling
pathways.",
crossref = "PMID:9888852"
}
@InProceedings{BellandHolcombe96,
author
= "A. Bell and M.
Holcombe",
editor
= "M. Holcombe and R. Paton
and R. Cuthbertson",
booktitle
= "Computation in Cellular and
Molecular Biological Systems: Selected Papers from {IPCAT} '95",
title
= "Computational models of
cellular processing",
publisher
= "World Scientific Press",
address
= "Singapore",
pages
= "",
year = "1996",
url = "http://www.dcs.shef.ac.uk/~wmlh/paper/biopaper.ps",
keywords
= "metabolism, statecharts,
quantitative, graphical",
abstract
= "A number of simple algebraic
models have been developed for the representation of basic metabolic processing
and related activities in cells. These tend to make gross assumptions about a
number of vital aspects of these complex dynamic systems. We present a
hierarchical model based on a general theory of computation which sets out to
model these systems without making many of these assumptions. We concentrate
then on modelling the specific resourcebased local metabolic processing that
lies at the bottom of this hierarchy.",
}
@Article{Bakeretal99,
author
= "P. G. Baker and C. A.
Goble and S. Bechhofer and N. W. Paton and R. Stevens and A. Brass",
title
= "An ontology for
bioinformatics applications",
journal
= "Bioinformatics",
year = "1999",
volume
= "15",
number
= "6",
pages
= "510--520",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/15/6/510.pdf",
keywords
= "ontology, object-oriented,
implementation, TAMBIS, TaO, GRAIL, description logic, logic,
compartment",
abstract
= "MOTIVATION: An ontology of
biological terminology provides a model of biological concepts that can be used
to form a semantic framework for many data storage, retrieval and analysis
tasks. Such a semantic framework could be used to underpin a range of important
bioinformatics tasks, such as the querying of heterogeneous bioinformatics
sources or the systematic annotation of experimental results. RESULTS: This
paper provides an overview of an ontology [the Transparent Access to Multiple
Biological Information Sources (TAMBIS) ontology or TaO] that describes a wide
range of bioinformatics concepts. The present paper describes the mechanisms
used for delivering the ontology and discusses the ontology's design and
organization, which are crucial for maintaining the coherence of a large
collection of concepts and their relationships. AVAILABILITY: The TAMBIS
system, which uses a subset of the TaO described here, is accessible over the
Web via http://img.cs.man.ac.uk/tambis (although in the first instance, we will
use a password mechanism to limit the load on our server). The complete model
is also available on the Web at the above URL.",
crossref
= "PMID:10383475",
}
@InProceedings{Bonoetal98,
author
= "H. Bono and S. Goto and W.
Fujibuchi and H. Ogata and M. Kanehisa",
title
= "Systematic Prediction of
Orthologous Units of Genes in the Complete Genomes",
booktitle
= "Genome Informatics",
volume
= "9,
pages
= "32-40",
year = "1998",
editor
= "K. Asai and S. Miyano and
T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.jsbi.org/journal/GIW98/GIW98F04.pdf",
keywords
= "KEGG, database, signaling,
metabolism, regulatory, reconstruction, pathway discovery, comparative",
abstract
= "In order to fully make use
of the vast amount of information in the complete genome sequences, we are
developing a genome-scale system for predicting gene functions and cellular
functions. The system makes use of the information of sequence similarity, the
information of positional correlations in the genome, and the reference
knowledge stored as the ortholog group tables in KEGG (Kyoto Encyclopedia of
Genes and Genomes). The ortholog group table summarizes orthologous and
paralogous relations among different organisms for a set of genes that are
considered to form a functional unit, such as a conserved portion of the metabolic
pathway or a molecular machinery for the membrane transport. At the moment, the
ortholog group table is constructed for the cases where the genes are clustered
in physically close positions in the genome for at least one organism. In this
paper, we describe the system and the actual analysis of the complete genome of
Pyrococcus horikoshii to identify ABC transporters.",
crossref
= "PMID:11072319",
}
@Article{Bonoetal00,
author
= "H. Bono and H. Ogata and
S. Goto and M. Kanehisa",
title
= "Reconstruction of amino
acid biosynthesis pathways from the complete genome sequence",
journal
= "Genome Research",
year = "1998",
volume
= "8",
number
= "3",
pages = "203--210",
url = "http://www.genome.org/cgi/reprint/8/3/203.pdf",
keywords
= "comparative, reconstruction,
graphical, metabolism, KEGG, database, pathway discovery",
abstract
= "The complete genome sequence
of an organism contains information that has not been fully utilized in the
current prediction methods of gene functions, which are based on piece-by-piece
similarity searches of individual genes. We present here a method that utilizes
a higher level information of molecular pathways to reconstruct a complete
functional unit from a set of genes. Specifically, a genome-by-genome
comparison is first made for identifying enzyme genes and assigning EC numbers,
which is followed by the reconstruction of selected portions of the metabolic
pathways by use of the reference biochemical knowledge. The completeness of the
reconstructed pathway is an indicator of the correctness of the initial gene
function assignment. This feature has become possible because of our efforts to
computerize the current knowledge of metabolic pathways under the KEGG project.
We found that the biosynthesis pathways of all 20 amino acids were completely
reconstructed in Escherichia coli, Haemophilus influenzae, and Bacillus
subtilis, and probably in Synechocystis and Saccharomyces cerevisiae as well,
although it was necessary to assume wider substrate specificity for aspartate
aminotransferases.",
crossref
= "PMID:9521924",
}
C
@InProceedings{Chen99,
author
= "T. Chen and V. Filkov and
S. S. Skiena",
title
= "Identifying Gene
Regulatory Networks from Experimental Data",
booktitle
= "Proceedings of RECOMB
‘99",
Series
= "",
volume
= "",
pages
= "",
year = "1999",
editor
= "",
publisher
= "",
address
= "",
url = "http://www.cs.sunysb.edu/~skiena/papers/genes.ps",
keywords
= "regulatory, reconstruction,
analysis, graph, pathway discovery, qualitative, implementation",
abstract = "In this paper, we propose a methodology for making sense of large, multiple timeseries data sets arising in expression analysis, and evaluate it both theoretically and through a case study. First, we build a graph representing all putative activation/inhibition relationships by analyzing the expression profiles for all pairs of genes. Second, we prune this graph by solving a combinatorial optimization problem to identify a small set of interesting candidate regulatory elements. We do not assert that we identify ``the'' regulatory network as a result of this computation. However, we believe that our approach quickly enables biologists to identify and visualize interesting features from raw expression array data sets. We have implemented our methodology and applied it to the analysis of the Saccharomyces cerevisiae data set.",
crossref
= "",
}
@InProceedings{CardenasGarciaetal00,
author
= "M. Cardenas-Garcia and J.
Lagunez-Otero and N. Korneev",
title
= "Efficient attractor
analysis based on self-dependent subsets of elements—an application to signal
transduction studies",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "8",
pages
= "86--92",
year = "2000",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "ftp://ftp.sdsc.edu/pub/sdsc/biology/ISMB00/140.pdf",
keywords
= "signaling, analysis, Boolean
network, modular, hierarchical, Self Determined Subset",
abstract
= "External signals are transmitted
to the cells through receptors activating signal transduction pathways. These
pathways form a complicated interconnected network, which is able to answer to
different stimuli. Here we analyze an important pathway for oncogenesis namely
RAS/MAPK signal transduction pathway. We show that the interaction of the
elements of this pathway induces topological structure in the element set and
that the knowledge of the topology simplifies the analysis of the set. With a
computer algorithm, we isolate from a large and complex group, smaller,
independent, more manageable subsets, and build their hierarchy. Subsets
introduction makes easier the search for attractors in discrete dynamical
system, it permits the prediction of final states for elements involved in
signal transduction pathways.",
crossref
= "PMID:10977069",
}
@InProceedings{Chenetal99,
author
= "T. Chen and H. L. He and
G. M. Church",
title
= "Modeling gene expression with
differential equations",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "29--40",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Chen.pdf",
keywords
= "kinetic, feedback,
regulatory, reconstruction",
abstract
= "We propose a differential
equation model for gene expression and provide two methods to construct the
model from a set of temporal data. We model both transcription and translation
by kinetic equations with feedback loops from translation products to
transcription. Degradation of proteins and mRNAs is also incorporated. We study
two methods to construct the model from experimental data: Minimum Weight
Solutions to Linear Equations (MWSLE), which determines the regulation by
solving under-determined linear equations, and Fourier Transform for Stable
Systems (FTSS), which refines the model with cell cycle constraints. The
results suggest that a minor set of temporal data may be sufficient to
construct the model at the genome level. We also give a comprehensive
discussion of other extended models: the RNA Model, the Protein Model, and the
Time Delay Model.",
crossref
= "PMID:10380183",
}
@Article{Clarkeetal93,
author
= "B. Clarke and J. E.
Mittenthal and M. Senn",
title
= "A model for the evolution
of networks of genes",
journal
= "Journal of Theoretical
Biology",
volume
= "165",
number
= "3",
pages
= "269--289",
year = "1993",
url = "",
keywords
= "Boolean network,
qualitative, regulatory, feedback, analysis, comparative, equivalence,
mutation, simulation, synchronous",
abstract
= "An organism persists through
the activity of structural genes, which is co-ordinated by clusters of coupled
regulatory genes. During evolution, changes of coupling within a cluster can
increase the reliability with which its structural genes perform a task. To
study the evolution of coupling, we have simulated and analyzed a stochastic
model for a simple problem. The assumptions of the model are these: A network
of regulatory genes co-ordinates the synthesis of four structural proteins,
which associate in distinct heterodimers that form a heterotetramer. Mutation
in cis-regulatory regions produces transitions among 64 types of network. In a
population, each network reproduces in proportion to its fitness, which depends
on its probability (reliability) of synthesizing the tetramer.
Fitness-dependent attrition keeps the size of the population constant.
Regulatory genes occur in a sequence of levels; each level is associated with a
different family of transcription factors. The following results emerge:
Because different messengers within a family can give networks with the same connectivity,
the 64 types of networks cluster into eight equivalence classes. During
evolution with a low mutation rate, high-fitness classes can be approached
through various paths on a fitness landscape. With a higher mutation rate,
networks remain more uniformly distributed among the 64 types, and
lower-fitness networks remain preponderant. An initially homogeneous population
becomes more heterogeneous through mutation, but selection according to fitness
later reduces its diversity. During this process the dispersion of the
population over the possible networks increases, then decreases as the
population approaches a unique steady state.",
crossref
= "PMID:8114498",
}
@Article{ColladoVidesetal98,
author
= "J. Collado-Vides and R. M. Gutierrez-Rios and G.
Bel-Enguix",
title
= "Networks of
transcriptional regulation encoded in a grammatical model",
journal
= "Biosystems",
volume
= "47",
number
= "1--2",
pages
= "103--118",
year = "1998",
url = "",
keywords
= "Grammar, logic, qualitative,
regulatory, analysis",
abstract
= "The work here presented
enriches a previous grammatical model of the transcriptional regulation of gene
expression. The previous model is centered on the representation of the
regulatory regions upstream of genes, and their internal organization in the
DNA. This paper is centered in discussing some alternatives related to the
representation of the organization of operons and their alternative states of
transcription, as active or inactive units of transcription. Transformational
rules can be used to describe the binding and unbinding of regulatory proteins,
and the associated representations of (ON/OFF) gene expression. The initial
representation of a regulated promoter is linked to that of the operon encoding
its regulatory protein. In this way the representation of a regulated operon
depends on that of all others regulating its transcription, enabling in principle
the encoding of regulatory networks within an expanded grammatical model of
gene regulation.",
crossref
= "PMID:9715754",
}
@Unpublished{cellml00,
author = "",
title = "The CellML Modeling Language",
year = "2000",
url = "http://www.cellml.org/public/about/what_is_cellml.html",
keywords
= "markup, quantitative, exchange, implementation, visualization,
simulation",
abstract
= "The CellML language is an
XML-based markup language being developed by Physiome Sciences Inc. in
Princeton, New Jersey, in conjunction with the Bioengineering Research Group at
the University of Auckland's Department of Engineering Science and affiliated
research groups. The purpose of CellML is to store and exchange computer-based
biological models. CellML allows scientists to share models even if they are
using different model-building software. It also enables them to reuse
components from one model in another, thus accelerating model building. CellML
includes information about model structure (how the parts of a model are
organizationally related to one another), mathematics (equations describing the
underlying biological processes) and metadata (additional information about the
model that allows scientists to search for specific models or model components
in a database or other repository). CellML includes mathematics and metadata by
leveraging existing languages, including MathML and RDF. In the future, CellML
may also use other existing languages to specify data and define simulation and
rendering information. The CellML project is closely affiliated with two other
XML-based language projects currently underway at the University of Auckland.
Combined, these languages will provide a complete vocabulary for describing
biological information at a range of resolutions from the subcellular to
organism level. AnatML is aimed at exchanging information at the organ level,
and has been used at the University of Auckland to store geometric information
and documentation that was generated during a skeleton digitization project.
FieldML can be used to describe spatially and temporally varying field
information using finite elements. It is appropriate for storing geometry
information inside AnatML, spatial distribution of parameters inside
compartments in CellML, or the spatial distribution of cellular model
parameters across an entire organ.",
}
D
@Article{Dandekaretal99,
author = "T. Dandekar and S. Schuster and B. Snel and M. Huynen and P. Bork",
title = "Pathway alignment: application to the comparative analysis
of glycolytic enzymes ",
journal
= "Biochemical Journal",
volume
= "343",
number
= "1",
pages
= "115--124",
year = "1999",
url = "http://www.biochemj.org/bj/343/0115/3430115.pdf",
keywords
= "metabolism, comparative,
pathway alignment, kinetic, analysis, flux route, whole genome, engineering,
steady state, topology, quantitative",
abstract
= "Comparative analysis of metabolic
pathways in different genomes yields important information on their evolution,
on pharmacological targets and on biotechnological applications. In this study
on glycolysis, three alternative ways of comparing biochemical pathways are
combined: (1) analysis and comparison of biochemical data, (2) pathway analysis
based on the concept of elementary modes, and (3) a comparative genome analysis
of 17 completely sequenced genomes. The analysis reveals a surprising
plasticity of the glycolytic pathway. Isoenzymes in different species are
identified and compared; deviations from the textbook standard are detailed.
Several potential pharmacological targets and by-passes (such as the
Entner-Doudoroff pathway) to glycolysis are examined and compared in the different
species. Archaean, bacterial and parasite specific adaptations are identified
and described.",
crossref
= "PMID:10493919",
}
@Article{Dhaeseleeretal00,
author
= "P. Dhaeseleer and S. Liang
and R. Somogyi",
title
= "Genetic network
inference: from co-expression clustering to reverse engineering",
journal
= "Bioinformatics",
volume
= "16",
number
= "8",
pages
= "707--726",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/8/707.pdf",
keywords
= "Boolean network,
reconstruction, kinetic, continuous, regulatory, linear",
abstract = "motivation: Advances in molecular
biological, analytical and computational technologies are enabling us to
systematically investigate the complex molecular processes underlying
biological systems. In particular, using high-throughput gene expression assays,
we are able to measure the output of the gene regulatory network. We aim here
to review datamining and modeling approaches for conceptualizing and unraveling
the functional relationships implicit in these datasets. Clustering of
co-expression profiles allows us to infer shared regulatory inputs and
functional pathways. We discuss various aspects of clustering, ranging from
distance measures to clustering algorithms and multiple-cluster memberships.
More advanced analysis aims to infer causal connections between genes directly,
i.e. who is regulating whom and how. We discuss several approaches to the
problem of reverse engineering of genetic networks, from discrete Boolean
networks, to continuous linear and non-linear models. We conclude that the combination
of predictive modeling with systematic experimental verification will be
required to gain a deeper insight into living organisms, therapeutic targeting
and bioengineering. ",
crossref
= "PMID:11099257",
}
@InProceedings{Dhaeseleeretal99,
author
= "P. DHaeseleer and X. Wen
and S. Fuhrman and R. Somogyi",
title
= "Linear modeling of mRNA
expression levels during CNS development and injury",
booktitle
= "Pacific Symposium on Biocomputing",
volume
= "4",
pages
= "41--52",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Dhaeseleer.pdf",
keywords
= "linear, reconstruction,
regulatory, continuous",
abstract
= "Large-scale gene expression
data sets are revolutionizing the field of functional genomics. However, few
data analysis techniques fully exploit this entirely new class of data. We
present a linear modeling approach that allows one to infer interactions
between all the genes included in the data set. The resulting model can be used
to generate interesting hypotheses to direct further experiments.",
crossref
= "PMID:10380184",
}
E
Article{Eisenbergetal00,
author
= "D. Eisenberg and E. M.
Marcotte and I. Xenarios and T. O. Yeates",
title = "Protein function in the post-genomic era",
journal
= "Nature",
volume
= "405",
number
= "6788",
pages
= "823--826",
year = "2000",
keywords
= "reconstruction,
protein-protein, metabolism, comparative, phylogenetic profile, domain,
interaction map, graph, analysis, whole genome, qualitative, pathway discovery,
Rosetta stone",
abstract
= "Faced with the avalanche of
genomic sequences and data on messenger RNA expression, biological scientists
are confronting a frightening prospect: piles of information but only flakes of
knowledge. How can the thousands of sequences being determined and deposited,
and the thousands of expression profiles being generated by the new array
methods, be synthesized into useful knowledge? What form will this knowledge
take? These are questions being addressed by scientists in the field known as
'functional genomics'.",
crossref
= "PMID:10866208",
}
@Article{Enright99,
author
= "A. J. Enright and I. Iliopoulos and N. C. Kyrpides
and C. A. Ouzounis ",
title = "Protein interaction maps for complete genomes based on
gene fusion events",
journal
= "Nature",
volume
= "402",
number
= "6757",
pages
= "86--90",
year = "1999",
keywords
= "protein-protein, interaction
map, graph, reconstruction, analysis, whole genome, qualitative, pathway
discovery",
abstract
= "A large-scale effort to
measure, detect and analyse protein-protein interactions using experimental
methods is under way. These include biochemistry such as co-immunoprecipitation
or crosslinking, molecular biology such as the two-hybrid system or phage
display, and genetics such as unlinked noncomplementing mutant detection. Using
the two-hybrid system, an international effort to analyse the complete yeast
genome is in progress. Evidently, all these approaches are tedious, labour
intensive and inaccurate. From a computational perspective, the question is how
can we predict that two proteins interact from structure or sequence alone.
Here we present a method that identifies gene-fusion events in complete
genomes, solely based on sequence comparison. Because there must be selective
pressure for certain genes to be fused over the course of evolution, we are
able to predict functional associations of proteins. We show that 215 genes or
proteins in the complete genomes of Escherichia coli, Haemophilus influenzae
and Methanococcus jannaschii are involved in 64 unique fusion events. The
approach is general, and can be applied even to genes of unknown
function.",
crossref
= "PMID:10573422",
}
@Unpublished{Erato00,
author = "",
title = "The Systems Biology Workbench
Software",
year = "2000",
url = "http://www.cds.caltech.edu/erato/workbench.html",
keywords
= "markup, kinetic, simulation,
implementation, quantitative, spatial, stoichiometry, regulatory, exchange,
systemic, UML, SBML, Gepasi, Dbsolve, Virtual Cell, E-cell, Gepasi, BioSpice,
Jarnac, BioSpice, StochSim, graphical, SBW, ERATO, object-oriented",
abstract
= "",
crossref
= "",
}
@InProceedings{ErbandMichaels99,
author
= "R. S. Erb and G. S.
Michaels",
title
= "Sensitivity of biological
models to errors in parameter estimates",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "53--64",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Erb.pdf",
keywords
= "analysis, robustness,
kinetic, grammar, spatial, neural network",
abstract
= "Since A. M. Turing's paper
proposing a mathematical basis for pattern formation in developing organisms
many mathematical approaches have been proposed to model biological phenomenon.
Continued laboratory study and recent improvements in measurement capabilities
have provided an immense quantity of raw gene expression data. The level of
data now available demands the development of well-characterized and tested
computational tools. Thus, we have examined one mathematical model's
sensitivity to errors in estimating its' parameters. Errors in parameter
estimation can arise from noise in the laboratory measurements and recasting of
laboratory data. We elected to examine the rule-based mathematical model of
Mjolsness et al for its' sensitivity to errors in estimated parameters. We have
used the technique of sensitivity equations as generally applied in nonlinear
systems analysis.",
crossref
= "PMID:10380185",
}
@Article{Edwardsetal01,
author
= "J. S. Edwards and R. U.
Ibarra and B. O. Palsson",
title = "In silico predictions of Escherichia coli metabolic
capabilities are consistent with experimental data",
journal
= "Nature Biotechnology",
volume
= "19",
number
= "2",
pages
= "125--130",
year = "2001",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing, phenotype
phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative",
abstract
= "A significant goal in the
post-genome era is to relate the annotated genome sequence to the physiological
functions of a cell. Working from the annotated genome sequence, as well as
biochemical and physiological information, it is possible to reconstruct
complete metabolic networks. Furthermore, computational methods have been
developed to interpret and predict the optimal performance of a metabolic
network under a range of growth conditions. We have tested the hypothesis that
Escherichia coli uses its metabolism to grow at a maximal rate using the E.
coli MG1655 metabolic reconstruction. Based on this hypothesis, we formulated
experiments that describe the quantitative relationship between a primary
carbon source (acetate or succinate) uptake rate, oxygen uptake rate, and
maximal cellular growth rate. We found that the experimental data were
consistent with the stated hypothesis, namely that the E. coli metabolic
network is optimized to maximize growth under the experimental conditions
considered. This study thus demonstrates how the combination of in silico and
experimental biology can be used to obtain a quantitative genotype-phenotype
relationship for metabolism in bacterial cells.",
crossref
= "PMID: 11175725",
}
@Article{EdwardsandPalsson99,
author
= "J. S. Edwards and B. O.
Palsson",
title
= "Systems properties of the
Haemophilus influenzae Rd metabolic genotype",
journal
= "Journal of Biological
Chemistry",
volume
= "274",
number
= "25",
pages
= "17410--17416",
year = "1999",
url = "http://www.jbc.org/cgi/reprint/274/25/17410.pdf",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing,
phenotype phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, mutation, phenotype phase
diagram",
abstract
= "Haemophilus influenzae Rd
was the first free-living organism for which the complete genomic sequence was
established. The annotated sequence and known biochemical information was used
to define the H. influenzae Rd metabolic genotype. This genotype contains 488
metabolic reactions operating on 343 metabolites. The stoichiometric matrix was
used to determine the systems characteristics of the metabolic genotype and to
assess the metabolic capabilities of H. influenzae. The need to balance
cofactor and biosynthetic precursor production during growth on mixed
substrates led to the definition of six different optimal metabolic phenotypes
arising from the same metabolic genotype, each with different constraining
features. The effects of variations in the metabolic genotype were also
studied, and it was shown that the H. influenzae Rd metabolic genotype contains
redundant functions under defined conditions. We thus show that the synthesis
of in silico metabolic genotypes from annotated genome sequences is possible
and that systems analysis methods are available that can be used to analyze and
interpret phenotypic behavior of such genotypes.",
crossref
= "PMID:10364169",
}
@Article{EdwardsandPalsson00,
author
= "J. S. Edwards and B. O.
Palsson",
title
= "Robustness analysis of
the escherichia coli metabolic network",
journal
= "Biotechnology
Progress",
volume
= "16",
number
= "6",
pages
= "927--939",
year = "2000",
url = "http://pubs.acs.org/isubscribe/journals/bipret/16/i06/pdf/bp0000712.pdf",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing,
phenotype phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, robustness",
abstract
= "Genomic, biochemical, and
strain-specific data can be assembled to define an in silico representation of
the metabolic network for a select group of single cellular organisms.
Flux-balance analysis and phenotypic phase planes derived there from have been
developed and applied to analyze the metabolic capabilities and characteristics
of Escherichia coli K-12. These analyses have shown the existence of seven
essential reactions in the central metabolic pathways (glycolysis, pentose
phosphate pathway, tricarboxylic acid cycle) for the growth in glucose minimal
media. The corresponding seven gene products can be grouped into three
categories: (1) pentose phosphate pathway genes, (2) three-carbon glycolytic
genes, and (3) tricarboxylic acid cycle genes. Here we develop a procedure that
calculates the sensitivity of optimal cellular growth to altered flux levels of
these essential gene products. The results indicate that the E.coli metabolic
network is robust with respect to the flux levels of these enzymes. The
metabolic flux in the transketolase and the tricarboxylic acid cycle reactions
can be reduced to 15% and 19%, respectively, of the optimal value without
significantly influencing the optimal growth flux. The metabolic network also
exhibited robustness with respect to the ribose-5-phosphate isomerase, and the
ribose-5-phosephate isomerase flux was reduced to 28% of the optimal value
without significantly effecting the optimal growth flux. The metabolic network
exhibited limited robustness to the three-carbon glycolytic fluxes both
increased and decreased. The development presented another dimension to the use
of FBA to study the capabilities of metabolic networks.",
crossref
= "PMID:11101318",
}
@Article{EdwardsandPalsson00a,
author
= "J. S. Edwards and B. O.
Palsson",
title
= "Metabolic flux balance
analysis and the in silico analysis of Escherichia coli K-12 gene
deletions",
journal
= "BMC Bioinformatics",
volume
= "1",
number
= "1",
pages
= "1--1",
year = "2000",
url = "http://biomedcentral.com/1471-2105/1/1",
keywords = "data representation, kinetic,
algebraic, biochemistry, stoichiometry, analysis, flux balancing, phenotype
phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative",
abstract
= "BACKGROUND: Genome
sequencing and bioinformatics are producing detailed lists of the molecular
components contained in many prokaryotic organisms. From this 'parts catalogue'
of a microbial cell, in silico representations of integrated metabolic
functions can be constructed and analyzed using flux balance analysis (FBA).
FBA is particularly well-suited to study metabolic networks based on genomic,
biochemical, and strain specific information. RESULTS: Herein, we have utilized
FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We
have computationally mapped the metabolic capabilities of E. coli using FBA and
examined the optimal utilization of the E. coli metabolic pathways as a
function of environmental variables. We have used an in silico analysis to
identify seven gene products of central metabolism (glycolysis, pentose
phosphate pathway, TCA cycle, electron transport system) essential for aerobic
growth of E. coli on glucose minimal media, and 15 gene products essential for
anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and
pta-mutant strains were examined in more detail by mapping the capabilities of
these in silico isogenic strains. CONCLUSIONS: We found that computational
models of E. coli metabolism based on physicochemical constraints can be used
to interpret mutant behavior. These in silica results lead to a further
understanding of the complex genotype-phenotype relation.Supplementary
information: http://gcrg.ucsd.edu/supplementary_data/
DeletionAnalysis/main.htm",
crossref
= "PMID:11001586",
}
@Article{EdwardsandPalsson00b,
author
= "J. S. Edwards and B. O.
Palsson",
title
= "The Escherichia coli
MG1655 in silico metabolic genotype: its definition,characteristics, and
capabilities",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "97",
number
= "10",
pages
= "5528--5533",
year = "2000",
url = "http://www.pubmedcentral.nih.gov/picrender.cgi?artid=8602&pictype=5",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing, phenotype
phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, mutation",
abstract
= "The Escherichia coli MG1655
genome has been completely sequenced. The annotated sequence, biochemical
information, and other information were used to reconstruct the E. coli
metabolic map. The stoichiometric coefficients for each metabolic enzyme in the
E. coli metabolic map were assembled to construct a genome-specific
stoichiometric matrix. The E. coli stoichiometric matrix was used to define the
system's characteristics and the capabilities of E. coli metabolism. The
effects of gene deletions in the central metabolic pathways on the ability of
the in silico metabolic network to support growth were assessed, and the in
silico predictions were compared with experimental observations. It was shown
that based on stoichiometric and capacity constraints the in silico analysis
was able to qualitatively predict the growth potential of mutant strains in 86%
of the cases examined. Herein, it is demonstrated that the synthesis of in
silico metabolic genotypes based on genomic, biochemical, and strain-specific
information is possible, and that systems analysis methods are available to
analyze and interpret the metabolic phenotype.",
crossref
= "PMID:10805808",
}
@Article{Ellisetal98,
author
= "L. B. Ellis and S. M.
Speedie and R. McLeish",
title
= "Representing metabolic
pathway information: an object-oriented approach",
journal
= "Bioinformatics",
year = "1998",
volume
= "14",
number
= "9",
pages
= "803--806",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/14/9/803.pdf",
keywords
= "object-oriented, database,
UM-BDD, metabolism, CORE, implementation, pathway discovery",
abstract
= "MOTIVATION: The University
of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) is a website
providing information and dynamic links for microbial metabolic pathways,
enzyme reactions, and their substrates and products. The Compound, Organism,
Reaction and Enzyme (CORE) object-oriented database management system was developed
to contain and serve this information. RESULTS: CORE was developed using Java,
an object-oriented programming language, and PSE persistent object classes from
Object Design, Inc. CORE dynamically generates descriptive web pages for
reactions, compounds and enzymes, and reconstructs ad hoc pathway maps starting
from any UM-BBD reaction. AVAILABILITY: CORE code is available from the authors
upon request. CORE is accessible through the UM-BBD at: http://www.
labmed.umn.edu/umbbd/index.html.",
crossref = "PMID:9918950",
}
@InProceedings{Eilbecketal99,
author
= "K. Eilbeck and A. Brass
and N. Paton and C. Hodgman",
title
= "INTERACT: an object
oriented protein-protein interaction database",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "7",
pages
= "87--94",
year = "1999",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "",
keywords
= "database, object-oriented,
protein-protein, implementation, INTERACT, UML, pathway discovery,
reconstruction, analysis, compartment",
abstract
= "MOTIVATION: Protein-protein
interactions provide vital information concerning the function of proteins, complexes
and networks. Currently there is no widely accepted repository of this
interaction information. Our aim is to provide a single database with the
necessary architecture to fully store, query and analyse interaction data.
RESULTS: An object oriented database has been created which provides scientists
with a resource for examining existing protein-protein interactions and
inferring possible interactions from the data stored. It also provides a basis
for examining networks of interacting proteins, via analysis of the data
stored. The database contains over a thousand interactions. ",
crossref
= "PMID:10786290",
}
@Article{Friedmanetal00,
author = "N. Friedman and M. Linial and I. Nachman and D. Pe'er",
title = "Using Bayesian networks to analyze expression data",
journal
= "Journal of Computational
Biology",
volume
= "7",
number
= "3--4",
pages
= "601--620",
year = "2000",
keywords
= "regulatory, reconstruction,
Bayesian network, inference, graph",
abstract
= "DNA hybridization arrays
simultaneously measure the expression level for thousands
of genes. These measurements provide a "snapshot" of transcription levels within the cell. A major challenge in
computational biology is to uncover, from such
measurements, gene/protein interactions and key biological features of cellular systems. In this paper, we
propose a new framework for discovering interactions
between genes based on multiple expression
measurements.
This framework builds on the use of Bayesian networks for representing statistical dependencies. A Bayesian
network is a graph-based model of joint multivariate
probability distributions that captures properties of conditional independence between variables. Such
models are attractive for their ability to describe complex
stochastic processes and because they provide a clear
methodology for learning from (noisy) observations. We start by showing how Bayesian networks can describe interactions
between genes. We then describe a method for recovering gene
interactions from microarray data using tools for learning
Bayesian networks. Finally, we demonstrate this method on the S. cerevisiae cell-cycle measurements of Spellman et
al. (1998).",
crossref
= "PMID:11108481",
}
@Article{Friedmanetal01,
author
= "C. Friedman and P. Kra and
H. Yu and M. Krauthammer and A. Rzhetsky",
title = "GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles.",
journal
= "Bioinformatics",
volume
= "17",
number
= "",
pages
= "S74--S82",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/suppl_1/S74.pdf",
keywords
= "ontology, signaling, regulatory,
visualization, biochemistry, knowledge representation, compartment, literature,
reconstruction, information extraction, implementation, GENIES, NLP",
abstract = "Systems that extract structured information from natural language passages have been highly successful in specialized domains. The time is opportune for developing analogous applications for molecular biology and genomics. We present a system, GENIES, that extracts and structures information about cellular pathways from the biological literature in accordance with a knowledge model that we developed earlier. We implemented GENIES by modifying an existing medical natural language processing system, MedLEE, and performed a preliminary evaluation study. Our results demonstrate the value of the underlying techniques for the purpose of acquiring valuable knowledge from biological journals.",
crossref
= "PMID:11472995",
}
@Article{ForstandSchulten01,
author
= "C. V. Forst and K. Schulten",
title = "Phylogenetic analysis of metabolic pathways",
journal
= "Journal of Molecular
Evolution",
volume
= "52",
number
= "6",
pages
= "471--489",
year = "2001",
url = "http://link.springer-ny.com/link/service/journals/00239/papers/1052006/10520471.pdf",
keywords
= "metabolism, comparative,
graph, whope genome, qualitative, pathway alignment, score",
abstract
= "The information provided by
completely sequenced genomes can yield insights into the multi-level
organization of organisms and their evolution. At the lowest level of molecular
organization individual enzymes are formed, often through assembly of multiple
polypeptides. At a higher level, sets of enzymes group into metabolic networks.
Much has been learned about the relationship of species from phylogenetic trees
comparing individual enzymes. In this article we extend conventional
phylogenetic analysis of individual enzymes in different organisms to the
organisms' metabolic networks. For this purpose we suggest a method that
combines sequence information with information about the underlying reaction
networks. A distance between pathways is defined as incorporating distances
between substrates and distances between corresponding enzymes. The new
analysis is applied to electron-transfer and amino acid biosynthesis networks
yielding a more comprehensive understanding of similarities and differences
between organisms.",
crossref
= "PMID:11443351",
}
@Article{FellandWagner,
author
= "D. A. Fell and A.
Wagner",
title = "The small world of metabolism",
journal
= "Nature Biotechnology",
volume
= "18",
number
= "11",
pages
= "1121--1122",
year = "2000",
keywords
= "metabolism, analysis, small
world, graph, quantitative, connectivity",
abstract
= "",
crossref
= "PMID:11062388",
}
@Article{Fujibuchi00,
author
= "W. Fujibuchi and H. Ogata
and H. Matsuda and M. Kanehisa",
title = "Automatic detection of conserved gene clusters in
multiple genomes by graph comparison and P-quasi grouping.",
journal
= "Nucleic Acids Research
",
volume
= "28",
number
= "20",
pages
= "4029--4036",
year = "2000",
url = "http://nar.oupjournals.org/cgi/reprint/28/20/4029.pdf",
keywords
= "graph, comparative,
analysis, KEGG, metabolism, whole genome, qualitative",
abstract
= "We previously reported two
graph algorithms for analysis of genomic information: a graph comparison
algorithm to detect locally similar regions called correlated clusters and an
algorithm to find a graph feature called P-quasi complete linkage. Based on
these algorithms we have developed an automatic procedure to detect conserved
gene clusters and align orthologous gene orders in multiple genomes. In the
first step, the graph comparison is applied to pairwise genome comparisons,
where the genome is considered as a one-dimensionally connected graph with
genes as its nodes, and correlated clusters of genes that share sequence
similarities are identified. In the next step, the P-quasi complete linkage
analysis is applied to grouping of related clusters and conserved gene clusters
in multiple genomes are identified. In the last step, orthologous relations of
genes are established among each conserved cluster. We analyzed 17 completely
sequenced microbial genomes and obtained 2313 clusters when the completeness
parameter P: was 40%. About one quarter contained at least two genes that
appeared in the metabolic and regulatory pathways in the KEGG database. This
collection of conserved gene clusters is used to refine and augment ortholog
group tables in KEGG and also to define ortholog identifiers as an extension of
EC numbers.",
crossref
= "PMID:11024184",
}
@TechReport{Finneyetal00,
author = "A. Finney and H. Sauro and M.
Hucka and H. Bolouri",
title = "An XML-Based Model Description
Language for Systems Biology Simulations",
institution = "California
Institute of Technology",
year = "2000",
month = "September",
note = "Technical report",
url = "ftp://ftp.cds.caltech.edu/pub/caltech-erato/sbml/sbml.pdf",
keywords
= "markup, kinetic, simulation,
implementation, quantitative, spatial, stoichiometry, regulatory, exchange,
systemic, UML, SBML, Gepasi, Dbsolve, Virtual Cell, E-cell, Gepasi, BioSpice,
Jarnac, BioSpice, StochSim, graphical, SBW, ERATO, object-oriented",
abstract = "We present a first attempt at specifying a common, model-based description language for systems biology simulation software. We call this the Systems Biology Markup Language (SBML).The overall goal is to develop an open standard that will enable simulation software to communicate and exchange models, ultimately leading to the ability for researchers to run simulations and analyses across multiple software packages. SBML is the result of merging the most obvious modeling-language features of BioSpice, DBSolve, E-Cell, Gepasi, Jarnac, StochSim, and Virtual Cell. The description language is encoded in XML, the Extensible Markup Language (Bosak and Bra ,1999;Bra ,Paoli and Sperberg-McQueen,1998). The XML encoding of the description language can define a file format; however, at this time, we are focusing on using the XML-based description language as an interchange format for use in communications between programs. The primary purpose of this document is to serve as a basis for discussion and further development of a more comprehensive language specification. The final outcome of this process will be an XML Schema which can be used to communicate model descriptions between simulation packages. Appendix B contains the current version of this schema. As XML Schemas are difficult to read and absorb by human readers, we define the proposed data structures using a succinct graphical notation based on a subset of UML, the Unified Modeling Language (Eriksson,1998;Oestereich,1999).Our notation is explained in A Notation for Describing Data Representations Intended for XML Encoding (Hucka,2000), available online at ftp://ftp.cds.caltech.edu/pub/caltech-erato/notation/. For the sake of clarity ,we ask readers to use this notation when contributing to discussions about the specification. To facilitate discussions, a web/FTP site and a group mailing list have been set up for the participating groups. Please see the web site at http://www.cds.caltech.edu/erato/for details.",
crossref
=
"http://www.cds.caltech.edu/erato/news/index.html",
}
@InProceedings{Freieretal00,
author
= "A. Freier and R. Hofestadt
and M. Lange and U. Scholz",
title
= "An Integrated Architecture
for Modeling and Simulation of Metabolic Networks",
booktitle
= "Proceedings of BIOTECHNOLOGY
2000",
Series
= "",
volume
= "1",
pages
= "210--211",
year = "2000",
editor
= "E. V. Dechema",
publisher = "",
address
= "",
url = "",
keywords
= "implementation, metabolism,
MARG, simulation, visualization",
abstract = "",
crossref
= "http://www-bm.cs.uni-magdeburg.de/iti_bm/marg/",
}
@InProceedings{Freieretal00a,
author
= "A. Freier and R. Hofestadt
and M. Lange and U. Scholz",
title
= "A component based architecture
for integration, modeling and animation of metabolic networks",
booktitle
= "Proceedings of the German
Conference on Bioinformatics (GCB'00)",
Series
= "",
volume
= "",
pages
= "",
year = "2000",
editor
= "",
publisher
= "",
address
= "",
url = "",
keywords
= "database, implementation,
metabolism, MARG, simulation, visualization",
abstract = "",
crossref
= "http://www-bm.cs.uni-magdeburg.de/iti_bm/marg/",
}
@InProceedings{Freieretal00b,
author
= "A. Freier and R. Hofestadt
and M. Lange and A. Stephanik",
title
= "MARGBench - Information Fusion
for Modeling and Simulation of Metabolic Networks",
booktitle
= "European Media Laboratory
(EML) Workshop on Scientific Databases",
Series
= "",
volume
= "",
pages
= "",
year = "2000",
editor
= "",
publisher
= "",
address
= "",
url = "",
keywords
= "database, implementation,
metabolism, MARG, simulation, visualization",
abstract = "",
crossref
= "http://www-bm.cs.uni-magdeburg.de/iti_bm/marg/",
}
@InProceedings{Freieretal99,
author
= "A. Freier and R. Hofestadt
and M. Lange and U. Scholz",
title
= "MARGBench - An Approach
for Integration, Modeling and Animation of Metabolic Networks",
booktitle
= "Proceedings of the German
Conference on Bioinformatics (GCB'99)",
Series
= "",
volume
= "",
pages
= "190--194",
year = "1999",
editor
= "R. Giegerich and R
Hofestadt and T. Lengauer and W. Mewes and D. Schomburg and M. Vingron and E.
Wingender",
publisher
= "",
address
= "",
url = "",
keywords
= "database, implementation, metabolism,
MARG, simulation, visualization, exchange, MetabSim, IMIS, MetabVis, database,
exchange",
abstract = "The development of the Integrative Molecular Information System (IMIS) for the metabolic networks is the goal of our MARG project. The architecture of our system allows information fusion based on different database systems. For the simulation of metabolic networks we use a rule-based simulation environment MetabSim, which enables the interactive simulation of biochemical networks. The idea of the project is to connect the simulation kernel with the database integration software.",
crossref
= "http://www-bm.cs.uni-magdeburg.de/iti_bm/marg/",
}
@InProceedings{Freieretal98,
author
= "A. Freier and M. Hading
and R. Hofestadt and M. Lange and U. Scholz ",
title
= "Molecular Database
Integration: Analysis of Metabolic Network Control ",
booktitle
= "Proceedings of the First
International Conference on Bioinformatics of Genome Regulation and Structure
(BGRS'98)",
Series
= "",
volume
= "1",
pages
= "86--89",
year = "1998",
editor
= "",
publisher
= "",
address
= "",
url = "",
keywords
= "analysis, metabolic control,
database, implementation, metabolism, MARG, MetabSim, IMIS",
abstract = "",
crossref
= "http://www-bm.cs.uni-magdeburg.de/iti_bm/marg/",
}
@InProceedings{Fellenbergetal00,
author
= "M. Fellenberg and K.
Albermann and A. Zollner and H. W. Mewes and J. Hani",
title
= "Integrative analysis of
protein interaction data",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "8",
pages
= "152--161",
year = "2000",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "ftp://ftp.sdsc.edu/pub/sdsc/biology/ISMB00/123.pdf
keywords
= "protein-protein,
reconstruction, visualization, database",
abstract
= "We have developed a method
for the integrative analysis of protein interaction data. It comprises
clustering, visualization and data integration components. The method is
generally applicable for all sequenced organisms. Here, we describe in detail
the combination of protein interaction data in the yeast Saccharomyces
cerevisiae with the functional classification of all yeast proteins. We
evaluate the utility of the method by comparison with experimental data and
deduce hypotheses about the functional role of so far uncharacterized proteins.
Further applications of the integrative analysis method are discussed. The
method presented here is powerful and flexible. We show that it is capable of
mining large-scale data sets.",
crossref
= "PMID:10977076",
}
@Article{ForstandSchulten99,
author
= "C. V. Forst and K.
Schulten",
title
= "Evolution of metabolisms:
a new method for the comparison of metabolic pathways using genomics
information",
journal
= "Journal of Computational
Biology",
volume = "6",
number
= "3--4",
pages
= "343--360",
year = "1999",
url = "http://www.ks.uiuc.edu/Publications/Papers/PDF/FORS99B/FORS99B.pdf",
keywords
= "comparative, metabolism,
graphical, topology",
abstract
= "The abundance of information
provided by completely sequenced genomes defines a starting point for new
insights in the multilevel organization of organisms and their evolution. At
the lowest level enzymes and other protein complexes are formed by aggregating
multiple polypeptides. At a higher level enzymes group conceptually into
metabolic pathways as part of a dynamic information-processing system, and
substrates are processed by enzymes yielding other substrates. A method based
on a combination of sequence information with graph topology of the underlying
pathway is presented. With this approach pathways of different organisms are
related to each other by phylogenetic analysis, extending conventional
phylogenetic analysis of individual enzymes. The new method is applied to
pathways related to electron transfer and to the Krebs citric acid cycle. In
addition to providing a more comprehensive understanding of similarities and
differences between organisms, this method indicates different evolutionary
rates between substrates and enzymes.",
crossref
= "PMID:10582571",
}
@InCollection{FontanaandBuss96,
author
= "W. Fontana and L. W.
Buss",
editor
= "J. Casti and A.
Karlqvist",
booktitle
= "Boundaries and
Barriers",
title
= "The barrier of objects:
From dynamical systems to bounded organizations ",
publisher
= "Addison-Wesley",
address
= "",
pages
= "56--116",
year = "1996",
url = "http://www.santafe.edu/~walter/Papers/barrier.US.ps.gz",
keywords
= "logic, linear logic,
biochemistry, lambda calculus, simulation, implementation, AlChemy, proof
nets",
abstract
= "Self-maintaining natural
systems include the global climate system, all living organisms, many cognitive
processes, and a diversity of human social institutions. The capacity to
construct artificial systems that are self-maintaining would be highly
desirable. Yet, curiously, there exists no readily identifiable scientific
tradition that seeks to understand what classes of such systems are possible or
to discover conditions necessary to achieve them. Given the ubiquity of such
systems naturally and the desirability of self-maintenance as a feature of
design, any credible approach to establishing such a tradition merits serious
attention. We have recently developed and implemented a framework for
approaching the problem (Fontana and Buss 1994a, Fontana and Buss 1994b). It is
based on the premise that the constituent entities of a self-maintaining system
characteristically engage in interactions whose direct outcome is the
construction of other entities in the same class. Self-maintenance, then, is
the consequence of a constructive feed-back loop: it occurs when the
construction processes induced by the entities of a system permit the
continuous regeneration of these same entities (Varela 1974). The specific
functional relationships between entities which collectively insure their
continuous regeneration, we define as an organization. A theory of
organization, so defined, is a theory of self-maintaining systems. A
prototypical instance of entities are molecules. And organisms are a
particularly interesting class of self-maintaining systems generated by their
constructive interactions. The atmosphere is another example. And so, perhaps,
is the sun at the nuclear level. The overarching long-term goal of our program
is to develop a formal understanding of self-maintaining organizations. Our
efforts in doing so, which we summarize here, have led us to appreciate a
fundamental problem in methodology: the traditional theory of "dynamical
systems" is not equipped for dealing with constructive processes. Indeed,
the very notion of "construction" requires a description that
involves the structure of objects. Yet, it was precisely the elimination of
objects from the formalism that make dynamical systems approaches so
tremendously successful. We seek to solve this impasse by connecting dynamical
systems with fundamental research in computer science, whose theoretical
foundations are about "objects" and their constructive
interrelations. Our long-term goal, then, becomes equivalent to the task of
expanding dynamical systems theory to include object construction, to become
what we have come to call constructive dynamical systems.",
crossref
= "",
}
@Article{Gleissetal00,
author
= "P. M. Gleiss and P. F.
Stadler and A. Wagner and D. A. Fell ",
title = "Small Cycles in Small Worlds",
journal
= "Physical Review
Letters",
volume
= "",
number
= "",
pages
= "",
note = "submitted"
year = "2000",
url = "http://www.santafe.edu/sfi/publications/Working-Papers/00-10-058.pdf",
keywords
= "metabolism, analysis, small
world, graph, quantitative, connectivity",
abstract
= "We characterize the
distributions of short cycles in a large metabolic network previously shown to
have small world characteristics and a power law degree distribution. Compared
with three classes of random networks, including Erdos-Renyi random graphs and
synthetic small world networks of the same connectivity, the metabolic network
has a particularly large number of triangles and a deficit in large cycles.
Short cycles reduce the length of detours when a connection is clipped, so we
propose that long cycles in metabolism may have been selected against in order
to shorten transition times and reduce the likelihood of oscillations in
response to external perturbations.",
crossref
= "",
}
@InProceedings{GossandPeccoud99,
author
= "P. J. E. Goss and J.
Peccoud",
title
= "Analysis of the
stabilizing effect of Rom on the genetic network controlling ColE1 plasmid
replication",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "65--76",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Goss.pdf",
keywords
= "Petri net, stochastic,
quantitative, simulation, regulatory, implementation, UltraSAN",
abstract
= "A stochastic model of ColE1
plasmid replication is presented. It is implemented by using UltraSAN, a simulation
tool based on an extension of stochastic Petri nets (SPNs). It allows an
exploration of the variation in plasmid number per bacterium, which is not
possible using a deterministic model. In particular, the rate at which
plasmid-free bacteria arise during bacterial division is explored in some
detail since spontaneous plasmid loss is a widely observed empirical
phenomenon. The rate of spontaneous plasmid loss provides an evolutionary
explanation for the maintainance of Rom protein. The presence of Rom acts to
reduce variance in plasmid copy number, thereby reducing the rate of plasmid
loss at bacterial division. The ability of stochastic models to link
biochemical function with evolutionary considerations is discussed.",
crossref
= "PMID:10380186",
}
@Article{GossandPeccoud98,
author
= "P. J. E. Goss and J.
Peccoud",
title
= "Quantitative modeling of
stochastic systems in molecular biology by using stochastic Petri nets",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "95",
number
= "12",
pages
= "6750--6755",
year = "1998",
url = "http://www.pnas.org/cgi/reprint/95/12/6750.pdf",
keywords
= "Petri net, stochastic,
quantitative, simulation, regulatory, implementation, UltraSAN",
abstract
= "An integrated understanding
of molecular and developmental biology must consider the large number of molecular
species involved and the low concentrations of many species in vivo.
Quantitative stochastic models of molecular interaction networks can be
expressed as stochastic Petri nets (SPNs), a mathematical formalism developed
in computer science. Existing software can be used to define molecular
interaction networks as SPNs and solve such models for the probability
distributions of molecular species. This approach allows biologists to focus on
the content of models and their interpretation, rather than their
implementation. The standardized format of SPNs also facilitates the
replication, extension, and transfer of models between researchers. A simple
chemical system is presented to demonstrate the link between stochastic models
of molecular interactions and SPNs. The approach is illustrated with examples
of models of genetic and biochemical phenomena where the ULTRASAN package is
used to present results from numerical analysis and the outcome of
simulations.",
crossref
= "PMID:9618484",
}
@Article{Goryaninetal99,
author
= "I. Goryanin I and T. C.
Hodgman and E. Selkov",
title
= "Mathematical simulation
and analysis of cellular metabolism and regulation",
journal
= "Bioinformatics",
volume
= "15",
number
= "9",
pages
= "749--758",
year = "1999",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/15/9/749.pdf",
keywords
= "kinetic, analysis,
metabolism, metabolic control, biochemistry, steady state, simulation,
implementation, DBsolve",
abstract
= "MOTIVATION: A better
understanding of the biological phenomena observed in cells requires the
creation and analysis of mathematical models of cellular metabolism and
physiology. The formulation and study of such models must also be simplified as
far as possible to cope with the increasing complexity demanded and exponential
accumulation of the metabolic reconstructions computed from sequenced genomes.
RESULTS: A mathematical simulation workbench, DBsolve, has been developed to
simplify the derivation and analysis of mathematical models. It combines: (i)
derivation of large-scale mathematical models from metabolic reconstructions
and other data sources; (ii) solving and parameter continuation of non-linear
algebraic equations (NAEs), including metabolic control analysis; (iii) solving
the non-linear stiff systems of ordinary differential equations (ODEs); (iv)
bifurcation analysis of ODEs; (v) parameter fitting to experimental data or
functional criteria based on constrained optimization. The workbench has been
successfully used for dynamic metabolic modeling of some typical biochemical
networks (Dolgacheva et al., Biochemistry (Moscow), 6, 1063-1068, 1996;
Goldstein and Goryanin, Mol. Biol. (Moscow), 30, 976-983, 1996), including
microbial glycolytic pathways, signal transduction pathways and receptor-ligand
interactions. AVAILABILITY: DBsolve 5. 00 is freely available from
http://websites.ntl.com/ approximately igor.goryanin.",
crossref
= "PMID:10498775",
}
@InProceedings{Goto97,
author
= "S. Goto and H. Bono and H.
Ogata and W. Fujibuchi and T. Nishioka and K. Sato and M. Kanehisa",
title
= "Organizing and Computing
Metabolic Pathway Data in Terms of Binary Relations",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "2",
pages
= "175--186",
year = "1997",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www-smi.stanford.edu/people/altman/psb97/goto.pdf",
keywords
= "binary, database, kegg,
metabolism, qualitative, implementation",
abstract
= "A new database system named
KEGG is being organized to computerize functional aspects of genes and genomes in
terms of the binary relations of interacting molecules or genes. We are
currently working on the metabolic pathway database that is composed of three
interconnected sections: genes, molecules, and pathways,which are also linked
to a number of existing databases through our DBGET retrieval system. Here we
present the basic concept of binary relations and hierarchical classifications
to represent the metabolic pathway data. The database operations are then
defined as an extension of the relational operations, and the path computation
problem is considered as a deduction from binary relations. An example of using
KEGG for the functional prediction of genomic sequences is presented.",
crossref
= "PMID:9390290",
}
H
@TechReport{Hucka00,
author = "M. Hucka",
title = "A notation for describing data
representations intended for XML encoding",
institution = "California
Institute of Technology",
year = "2000",
month = "September",
note = "Technical report",
url = "ftp://ftp.cds.caltech.edu/pub/caltech-erato/notation/notation.pdf",
keywords
= "markup, kinetic, simulation,
implementation, quantitative, spatial, stoichiometry, regulatory, exchange,
systemic, UML, SBML, Gepasi, Dbsolve, Virtual Cell, E-cell, Gepasi, BioSpice,
Jarnac, BioSpice, StochSim, graphical, SBW, ERATO, object-oriented",
abstract = "One component of the ERATO Kitano Systems Biology Project is the creation of a workbench that provides interoperability between a number of simulation packages. Developing a framework for database storage and inter-program exchange requires defining a language for communicating data. Defining this language requires first establishing a notation that humans can use to describe the data structures involved. I propose a simple notation to be used for describing data structures that are intended to be encoded using XML, the Extensible Markup Language (Bosak and Bra ,1999;Bra ,Paoli and Sperberg-McQueen, 1998;Fallside,2000). The notation is based in part on a small subset of UML, the Unified Modeling Language (Eriksson,1998;Oestereich,1999),a visual language for specifying software systems. There are three main advantages to using UML class diagrams as a basis for defining data structures. First, compared to using other notations or a programming language, the UML visual representations are generally easier to read and understand b readers who are not computer scientists. Second, the visual notation is implementation- neutral —the defined structures can be encoded in an concrete implementation language, not just XML but other formats as well, making the UML-based definitions more useful and flexible. Third, UML is a de facto industry standard (OMG,2000),documented in man books and available in man software tools including mainstream development environments (such as Microsoft Visual Basic 5 Enterprise Edition).Readers are therefore more likely to be familiar with it than other notations.",
crossref
=
"http://www.cds.caltech.edu/erato/news/index.html",
}
@Article{HofestadtandThelen98,
author
= "R. Hofestadt and S.
Thelen",
title = "Quantitative Modeling of Biochemical Networks",
journal
= "In Silico Biology",
volume
= "1",
number
= "1",
pages
= "39--53",
year = "1998",
url = "http://www.bioinfo.de/isb/1998/01/0006/",
keywords
= "quantitative, metabolism,
simulation, Petri net",
abstract
= "Today different database
systems for molecular structures (genes and proteins) and metabolic pathways
are available. All these systems are characterized by the static data
representation. For progress in biotechnology, the dynamic representation of
this data is important. The metabolism can be characterized as a complex
biochemical network. Different models for the quantitative simulation of
biochemical networks are discussed, but no useful formalization is available.
This paper shows that the theory of Petrinets is useful for the quantitative
modeling of biochemical networks.",
crossref
= "",
}
@Article{Hofestadt98,
author
= "R. Hofestadt",
title = "A integrative molecular information system",
journal
= "Medinfo",
volume
= "9",
number
= "1",
pages
= "361--364",
year = "1998",
url = "",
keywords
= "database, molecular,
regulatory, implementation, IMIS",
abstract
= "Methods of biotechnology
allow the isolation, sequencing, and synthesis of molecular structures.
Molecular database systems are available, which allow the worldwide data
access. Methods and concepts of bioinformatics are important for the analysis
of these molecular data, which represent complex regulatory networks. In this
paper we present the architecture of our molecular information system.",
crossref
= "PMID:10384478",
}
@Article{HofestadtandMeineke95,
author
= "R. Hofestadt and F.
Meineke",
title = "Interactive modeling and simulation of biochemical
networks.",
journal = "Commputational Biology and Medicine",
volume
= "25",
number
= "3",
pages
= "321--334",
year = "1995",
url = "",
keywords
= "simulation, metabolism,
interactive, implementation, MARG, MetabSim, IMIS",
abstract
= "The analysis of biochemical
processes can be supported using methods of modelling and simulation. New
methods of computer science are discussed in this field of research. This paper
presents a new method which allows the modeling and analysis of complex
metabolic networks. Moreover, our simulation shell is based on this
formalization and represents the first tool for the interactive simulation of
metabolic processes.",
crossref
= "PMID:7554849",
}
@InProceedings{Hofestadt93,
author
= "R. Hofestadt",
title
= "Grammatical formalization
of metabolic processes",
booktitle
= " Intelligent Systems for
Molecular Biology",
volume
= "1",
pages
= "181--189",
year = "1993",
editor
= "",
publisher
= "AAAI Press",
address
= "",
url = "",
keywords
= "metabolism, grammar,
graph",
abstract
= "In the field of
biotechnology and medicine it is of interest to model and simulate metabolic
processes. The usual methods to model metabolic pathways are chemical
descriptions and differential equations. Moreover, the graph theoretical aspect
is discussed and the development of expert systems is in process. In this paper
we present the formalization of metabolic processes. Our formalization is based
on the theory of formal languages. This formalization is called genetic grammar
and represents an expansion of the Semi-Thue-System.",
crossref
= "PMID:7584334",
}
@Article{HeinrichandSchuster98,
author
= "R. Heinrich and S.
Schuster",
title = "The modeling of metabolic systems. Structure, control
and optimality",
journal
= "Biosystems",
volume
= "47",
number
= "1--2",
pages
= "61--77",
year = "1998",
url = "",
keywords
= "metabolism, kinetic,
analysis, biochemistry, steady state, flux balancing, flux route, modular,
algebraic, pathway discovery, temporal, optimization, metabolic control,
quantitative",
abstract
= "This article gives an
overview of recent developments in the modelling of the structure, control and
optimality of metabolic networks. In particular, methods of algebraically
analyzing the topology of such networks are presented. By these methods,
conservation relations and elementary modes of functioning (biochemical routes)
can be detected. The principles of metabolic control analysis are outlined.
Various recent extensions of this theory are presented, such as an analysis in
terms of time dependent variables and modular analysis. Evolutionary
optimization principles are applied to explain the catalytic efficiency of
single enzymes as well as the structural design of metabolic pathways. Special
results concern the optimal distribution of ATP consuming and ATP producing
reactions in glycolysis.",
crossref
= "PMID:9715751",
}
@InProceedings{Humphreysetal00,
author
= "K. Humphreys and G. Demetriou
and R. Gaizauskas",
title
= "Two applications of
information extraction to biological science journal articles: enzyme
interactions and protein structures",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "5",
pages
= "505--516",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/humphreys.pdf",
keywords
= "reconstruction, pathway
discovery, NLP, literature, biochemistry, information extraction,
implementation, EMPathIE",
abstract = "Information extraction technology,
as defined and developed through the U.S. DARPA Message Understanding
Conferences (MUCs), has proved successful at extracting information primarily
from newswire texts and primarily in domains concerned with human activity. In
this paper we consider the application of this technology to the extraction of
information from scientific journal papers in the area of molecular biology. In
particular, we describe how an information extraction system designed to
participate in the MUC exercises has been modified for two bioinformatics
applications: EMPathIE, concerned with enzyme and metabolic pathways; and
PASTA, concerned with protein structure. Progress to date provides convincing
grounds for believing that IE techniques will deliver novel and effective ways
for scientists to make use of the core literature which defines their
disciplines.",
crossref
= "PMID:10902198",
}
@InProceedings{Harteminketal01,
author
= "A.J. Hartemink and D.K.
Gifford and T.S. Jaakkola and R.A. Young",
title
= "Using Graphical Models
and Genomic Expression Data to Statistically Validate Models of Genetic
Regulatory Networks",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "6",
pages
= "422--433",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/hartemink.pdf",
keywords
= "reconstruction, Bayesian
network, graphical, regulatory, comparative, equivalence, score",
abstract
= "We propose a model-driven
approach for analyzing genomic expression data that permits genetic regulatory
networks to be represented in a biologically interpretable computational form.
Our models permit latent variables capturing unobserved factors, describe
arbitrarily complex (more than pair-wise) relationships at varying levels of
refinement, and can be scored rigorously against observational data. The models
that we use are based on Bayesian networks and their extensions. As a
demonstration of this approach, we utilize 52 genomes worth of Affymetrix
GeneChip expression data to correctly differentiate between alternative
hypotheses of the galactose regulatory network in S. cerevisiae. When we extend
the graph semantics to permit annotated edges, we are able to score models
describing relationships at a finer degree of specification.",
crossref
= "",
}
@InProceedings{HeidtkeandSchulzeKremer99,
author
= "K. R. Heidtke and S.
Schulze-Kremer",
title
= "Deriving simulation models from a molecular biology
knowledge base",
booktitle
= "Proceeding of the 4th
Workshop on Engineering Problems for Qualitative Reasoning of the 16th
International Joint Conference on Artificial Intelligence",
volume = "",
pages
= "",
year = "1999",
editor
= "",
publisher
= "",
address
= "",
url =
"http://igd.rz-berlin.mpg.de/~steffen/krh-ssk-ijcaiKRR4.ps.gz",
keywords
= "qualitative, logic,
simulation, implementation, BioSim, analysis, inference,
metabolism,semi-quantitative, object-oriented, database, constraint, model
description language",
abstract
= "Qualitative reasoning has
been proven a powerful technique to represent the relations between components
and objects of physical processes. This technique is of great interest for
simulation of biological processes where detailed quantitative information is
not available and only qualitative or fuzzy statements about the nature of
interactions are known. Model building is an inevitable and time consuming task
that even can turn the building of a putatively simple model into a major task.
To facilitate this task, we present a new Model Description Language, MDL, to
describe templates that can be used to translate a selected item of interest
from a molecular biology knowledge base into simulation objects and processes.
This is done by use of the presented Model Description Interpreter, MDI. We
show that qualitative reasoning can be combined with automatic transformation
of contents of genomic databases into simulation models to give an interactive
modelling system that reasons about the relations and interactions of
biological entities",
crossref
= "",
}
@Article{HeidtkeandSchulzeKremer98,
author
= "K. R. Heidtke and S.
Schulze-Kremer",
title
= "Design and implementation
of a qualitative simulation model of lambda phage infection",
journal
= "Bioinformatics",
volume
= "14",
number = "1",
pages
= "81--91",
year = "1998",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/14/1/81.pdf",
keywords
= "qualitative, logic,
simulation, implementation, QSim, analysis, inference, regulatory",
abstract
= "MOTIVATION: Molecular
biology databases hold a large number of empirical facts about many different
aspects of biological entities. That data is static in the sense that one
cannot ask a database 'What effect has protein A on gene B?' or 'Do gene A and
gene B interact, and if so, how?'. Those questions require an explicit model of
the target organism. Traditionally, biochemical systems are modelled using
kinetics and differential equations in a quantitative simulator. For many
biological processes however, detailed quantitative information is not
available, only qualitative or fuzzy statements about the nature of
interactions. RESULTS: We designed and implemented a qualitative simulation
model of lambda phage growth control in Escherichia coli based on the existing
simulation environment QSim. Qualitative reasoning can serve as the basis for
automatic transformation of contents of genomic databases into interactive modelling
systems that can reason about the relations and interactions of biological
entities.",
crossref
= "PMID:9520505",
}
@InProceedings{HeidtkeandSchulzeKremer98,
author
= "K. R. Heidtke and S. Schulze-Kremer",
title
= "BioSim--a new qualitative
simulation environment for molecular biology",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "6",
pages
= "85--94",
year = "1998",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "http://igd.rz-berlin.mpg.de/~steffen/BioSim.ps.gz",
keywords
= "qualitative, logic,
simulation, implementation, BioSim, analysis, inference",
abstract
= "Traditionally, biochemical
systems are modelled using kinetics and differential equations in a
quantitative simulator. However, for many biological processes detailed
quantitative information is not available, only qualitative or fuzzy statements
about the nature of interactions. In a previous paper we have shown the
applicability of qualitative reasoning methods for molecular biological
regulatory processes. Now, we present a newly developed simulation environment,
BioSim, that is written in Prolog using constraint logic programming
techniques. The simulator combines the basic ideas of two main approaches to
qualitative reasoning and integrates the contents of a molecular biology
knowledge base, EcoCyc. We show that qualitative reasoning can be combined with
automatic transformation of contents of genomic databases into simulation
models to give an interactive modelling system that reasons about the relations
and interactions of biological entities. This is demonstrated on the glycolytic
pathway.",
crossref
= "PMID:9783213",
}
@Article{Hastyetal00,
author
= "J. Hasty and J. Pradines
and M. Dolnik and J. J. Collins",
title
= "Noise-based switches and
amplifiers for gene expression",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "97",
number
= "5",
pages
= "2075--2080",
year = "2000",
url = "http://www.pnas.org/cgi/reprint/97/5/2075",
keywords
= "simulation, kinetic,
biochemical, regulatory",
abstract
= "The regulation of cellular
function is often controlled at the level of gene transcription. Such genetic
regulation usually consists of interacting networks, whereby gene products from
a single network can act to control their own expression or the production of
protein in another network. Engineered control of cellular function through the
design and manipulation of such networks lies within the constraints of current
technology. Here we develop a model describing the regulation of gene
expression and elucidate the effects of noise on the formulation. We consider a
single network derived from bacteriophage lambda and construct a two-parameter
deterministic model describing the temporal evolution of the concentration of
lambda repressor protein. Bistability in the steady-state protein concentration
arises naturally, and we show how the bistable regime is enhanced with the
addition of the first operator site in the promotor region. We then show how
additive and multiplicative external noise can be used to regulate expression.
In the additive case, we demonstrate the utility of such control through the
construction of a protein switch, whereby protein production is turned
"on" and "off" by using short noise pulses. In the
multiplicative case, we show that small deviations in the transcription rate
can lead to large fluctuations in the production of protein, and we describe
how these fluctuations can be used to amplify protein production significantly.
These results suggest that an external noise source could be used as a switch
and/or amplifier for gene expression. Such a development could have important
implications for gene therapy.",
crossref = "PMID:10681449",
}
@InProceedings{HolcombeandBell98,
author
= "M. Holcombe and A.
Bell",
editor
= "M. Holcombe and R.
Paton",
booktitle
= "Information Processing in
Cells and Tissues: Proceeding of {IPCAT} '97",
title
= "Computational models of
immunological pathways",
publisher
= "Plenum Press",
address
= "New York",
pages
= "213--226",
year = "1998",
url = "http://www.dcs.shef.ac.uk/~wmlh/paper/immuno.ps",
keywords
= "statecharts, graphical,
implementation, immune, signaling",
abstract
= "A computational model of part
of the immune system is introduced. The model is novel in respect of it
representing the populations of the T cells and other related components of the
system as a statebased parallel model. This is then analysed with respect to
possible spatial and temporal interactions with the result of a number of
simulations are presented and some conclusions drawn. One of the interesting
aspects of the work is the attempt to construct an integrative model of a
complex dynamic system such as the immune system. ",
}
I
@Article{Ichikawa01,
author
= "K. Ichikawa",
title = "A-Cell: graphical user interface for the construction of biochemical reaction",
journal
= "Bioinformatics",
volume
= "17",
number
= "5",
pages
= "483--484",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/5/483.pdf",
keywords
= "implementation, A-Cell, visualization, biochemistry,
graphical, graph, simulation, quantitative, continous, kinetic,
biochemistry",
abstract
= "SUMMARY: A-Cell is a tool
for constructing models of complex and complicated biochemical reactions. An important
feature of A-Cell is its graphical user interface for constructing biochemical
reactions. In addition, it has a capability of importing previously constructed
models, combining them, and constructing a comprehensive model. The simulation
program for the model is automatically generated by A-cell.",
crossref
= "PMID:11331245",
}
@Article{Idekeretal01,
author = "T. Ideker and V. Thorsson and J. A. Ranish and R. Christmas and J. Buhler and J. K. Eng and R. Bumgarner and D. R. Goodlett DR and R. Aebersold and L. Hood L.", title = "Integrated genomic and proteomic analyses of a systematically perturbed metabolic network ",
journal
= "Science",
volume
= "292",
number
= "5518",
pages
= "929--934",
year = "2001",
url = "http://www.sciencemag.org/cgi/reprint/292/5518/929.pdf",
keywords
= "metabolism, whole genome,
reconstruction, graph, protein-protein, graphical, regulatory, biochemistry,
semi-quantitative, mutation",
abstract
= "We demonstrate an integrated
approach to build, test, and refine a model of a cellular pathway, in which
perturbations to critical pathway components are analyzed using DNA
microarrays, quantitative proteomics, and databases of known physical
interactions. Using this approach, we identify 997 messenger RNAs responding to
20 systematic perturbations of the yeast galactose-utilization pathway, provide
evidence that approximately 15 of 289 detected proteins are regulated
posttranscriptionally, and identify explicit physical interactions governing
the cellular response to each perturbation. We refine the model through further
iterations of perturbation and global measurements, suggesting hypotheses about
the regulation of galactose utilization and physical interactions between this
and a variety of other metabolic pathways.",
crossref
= "PMID:11340206",
}
@InProceedings{Idekeretal00,
author
= "T. E. Ideker and V.
Thorsson and R. M. Karp",
title
= "Discovery of regulatory
interactions through perturbation: inference and experimental design",
booktitle
= "Pacific Symposium on Biocomputing",
volume
= "5",
pages
= "305--316",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/ideker.pdf",
keywords
= "reconstruction, Boolean
network, steady state, regulatory, mutation",
abstract
= "We present two methods to be
used interactively to infer a genetic network from gene expression
measurements. The predictor method determines the set of Boolean networks
consistent with an observed set of steady-state gene expression profiles, each
generated from a different perturbation to the genetic network. The chooser
method uses an entropy-based approach to propose an additional perturbation
experiment to discriminate among the set of hypothetical networks determined by
the predictor. These methods may be used iteratively and interactively to
successively refine the genetic network: at each iteration, the perturbation
selected by the chooser is experimentally performed to generate a new gene
expression profile, and the predictor is used to derive a refined set of
hypothetical gene networks using the cumulative expression data. Performance of
the predictor and chooser is evaluated on simulated networks with varying
number of genes and number of interactions per gene.",
crossref
= "PMID:10902179",
}
@InProceedings{IgarashiandKaminuma97,
author
= "T. Igarashi and T.
Kaminuma",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
booktitle
= "Proccedings of the Pacific Symposium
of Biocomputing '97",
title
= "Development of a cell
signalling networks database",
publisher
= "World Scientific Press",
address
= "Singapore",
pages
= "187--197",
year = "1997",
url = "http://www-smi.stanford.edu/people/altman/psb97/igarashi.pdf",
keywords
= "database, CSNDB, graph,
signaling, qualitative,implementation",
abstract
= "In multicellular organisms
cell signaling networks play important roles in wide range of biological
phenomena, such as development, differentiation, reproduction, morphogenesis,
carcinogenesis, apoptosis, and even learning. In order to explain biological
phenomena based on cell signaling models, we have developed a database for cell
signaling networks. The system contains mechanisms of signal transduction and
structure and functional data and references of extracellular chemicals and
biomolecules. CSNDB is constructed using ACEDB system, and includes various
graphical representations such as pathway diagrams, mapdiagrams, 3-D images,
pictures, and VRML environment. The system will be useful for modeling cells
and their information processing, and to explain important biological phenomena
based on these models.",
crossref
= "PMID:9390291",
}
@Article{IgarahiandKaminuma99,
author
= "T. T. Igarashi and T.
Kaminuma",
title
= "A Pathway Finding System
for the Cell Signaling Networks Database",
journal
= "In Silico Biology",
year = "1999",
volume
= "1",
number
= "",
pages
= "129--146",
url = "http://www.bioinfo.de/isb/1998/01/0012/main.html",
keywords
= "database, CSNDB, graph,
signaling, qualitative,implementation, pathway discovery, inference",
abstract
= "We report on a
knowledge-based pathway-finding system that builds on the cell-signaling
networks database, CSNDB, which we developed previously. This new system,
PaF-CSNDB, uses a general inference engine to apply rules for finding and
coupling pathways between or around specific biomolecules from the CSNDB
database. We show how PaF-CSNDB finds relationships in a large but fragmented
collection of cell-signaling knowledge by filtering out and composing together
those sections of pathways specified from an extensive and complex set of
binary or pair-wise cell-signaling reactions. The system can be accessed over
the World Wide Web.",
}
J
@Article{Jenssenetal01,
author
= "T.K. Jenssen and A.
Laegreid and J. Komorowski and E. Hovig",
title = "A literature network of human genes for high-throughput analysis of gene ",
journal
= "Nature Genetics",
volume
= "28",
number
= "1",
pages
= "21--28",
year = "2001",
url = "http://www.nature.com/cgi-taf/DynaPage.taf?file=/ng/journal/v28/n1/full/ng0501_21.html&filetype=pdf",
keywords
= "literature, information
extraction, reconstruction, "implementation, PubGenegraph, regulatory,
whole genome
abstract
= "We have carried out
automated extraction of explicit and implicit biomedical knowledge from
publicly available gene and text databases to create a gene-to-gene co-citation
network for 13,712 named human genes by automated analysis of titles and
abstracts in over 10 million MEDLINE records. The associations between genes
have been annotated by linking genes to terms from the medical subject heading
(MeSH) index and terms from the gene ontology (GO) database. The extracted database
and accompanying web tools for gene-expression analysis have collectively been
named 'PubGene'. We validated the extracted networks by three large-scale
experiments showing that co-occurrence reflects biologically meaningful
relationships, thus providing an approach to extract and structure known
biology. We validated the applicability of the tools by analyzing two publicly
available microarray data sets.",
crossref
= "PMID:11326270",
}
@Article{Jamshidietal01,
author
= "N. Jamshidi and J. S.
Edwards and T. Fahland and G. M. Church and B. O. Palsson",
title = "Dynamic simulation of the human red blood cell metabolic network",
journal
= "Bioinformatics",
volume = "17",
number
= "3",
pages
= "286--287",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/3/286.pdf",
keywords
= "metabolism, simulation,
quantitative, kinetic, implementation, analysis, continous",
abstract
= "We have developed a
Mathematica application package to perform dynamic simulations of the red blood
cell (RBC) metabolic network. The package relies on, and integrates, many years
of mathematical modeling and biochemical work on red blood cell metabolism. The
extensive data regarding the red blood cell metabolic network and the previous
kinetic analysis of all the individual components makes the human RBC an ideal
'model' system for mathematical metabolic models. The Mathematica package can
be used to understand the dynamics and regulatory characteristics of the red
blood cell.",
crossref
= "PMID:11294796",
}
@Article{JainandKrishna,
author
= "S. Jain and S.
Krishna",
title = "A model for the emergence of cooperation, interdependence, and structure in evolving networks",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "98",
number
= "2",
pages
= "543--547",
year = "2001",
url = "http://www.pnas.org/cgi/reprint/98/2/543.pdf",
keywords
= "comparative, graph,
regulatory, metabolism, analysis",
abstract
= "Evolution produces complex
and structured networks of interacting components in chemical, biological, and
social systems. We describe a simple mathematical model for the evolution of an
idealized chemical system to study how a network of cooperative molecular
species arises and evolves to become more complex and structured. The network
is modeled by a directed weighted graph whose positive and negative links
represent "catalytic" and "inhibitory" interactions among
the molecular species, and which evolves as the least populated species
(typically those that go extinct) are replaced by new ones. A small
autocatalytic set, appearing by chance, provides the seed for the spontaneous
growth of connectivity and cooperation in the graph. A highly structured
chemical organization arises inevitably as the autocatalytic set enlarges and
percolates through the network in a short analytically determined timescale.
This self organization does not require the presence of self-replicating
species. The network also exhibits catastrophes over long timescales triggered
by the chance elimination of "keystone" species, followed by
recoveries.",
crossref
= "PMID:11149953",
}
@Article{Jeongetal00,
author
= "H. Jeong and B. Tombor and
R. Albert and Z. N. Oltvai and A. L. Barabasi",
title = "The large-scale organization of metabolic networks
",
journal
= "Nature",
volume
= "407",
number
= "6804",
pages
= "651--654",
year = "2000",
keywords
= "metabolism, analysis,
systemic, comparative, robustness, topology",
abstract
= "In a cell or microorganism,
the processes that generate mass, energy, information transfer and cell-fate
specification are seamlessly integrated through a complex network of cellular
constituents and reactions. However, despite the key role of these networks in
sustaining cellular functions, their large-scale structure is essentially
unknown. Here we present a systematic comparative mathematical analysis of the
metabolic networks of 43 organisms representing all three domains of life. We
show that, despite significant variation in their individual constituents and pathways,
these metabolic networks have the same topological scaling properties and show
striking similarities to the inherent organization of complex non-biological
systems. This may indicate that metabolic organization is not only identical
for all living organisms, but also complies with the design principles of
robust and error-tolerant scale-free networks, and may represent a common
blueprint for the large-scale organization of interactions among all cellular
constituents.",
crossref
= "PMID:11034217",
}
K
@Article{Kaliretal01,
author = "S. Kalir and J. McClure and K. Pabbaraju and C. Southward and M. Ronen and S. Leibler and M. G. Surette and U. Alon", title = "Ordering genes in a flagella pathway by analysis of expression kinetics from living bacteria ",
journal
= "Science",
volume
= "292",
number
= "5524",
pages
= "2080--2083",
year = "2001",
url = "http://www.sciencemag.org/cgi/reprint/292/5524/2080.pdf",
keywords
= "reconstruction, molecular,
kinetic, temporal, analysis, continous",
abstract
= "The recent advances in
large-scale monitoring of gene expression raise the challenge of mapping
systems on the basis of kinetic expression data in living cells. To address
this, we measured promoter activity in the flagellar system of Escherichia coli
at high accuracy and temporal resolution by means of reporter plasmids. The
genes in the pathway were ordered by analysis algorithms without dependence on
mutant strains. The observed temporal program of transcription was much more
detailed than was previously thought and was associated with multiple steps of
flagella assembly.",
crossref
= "PMID:11408658",
}
@InProceedings{Karpetal96,
author
= "P. D. Karp and C. Ouzounis
and S. Paley",
title
= "HinCyc: A Knowledge Base
of the Complete Genome and Metabolic Pathways of H. influenzae ",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "4",
pages
= "116—124",
year = "1996",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "http://www.ai.sri.com/pubs/papers/Karp96:HinCyc/document.ps",
keywords
= "metabolism, database,
implementation, HinCyc, reconstruction, pathway discovery, inference, whole
genome, frames",
abstract = "We present a methodology for predicting the metabolic pathways of an organism from its genomic sequence by reference to a knowledge base of known metabolic pathways. We applied these techniques to the genome of H. influenzae by reference to the EcoCyc knowledge base to predict which of 81 metabolic pathways of E. coli are found in H. influenzae. The resulting prediction is a complex hypothesis that is presented in computer form as HinCyc: an electronic encyclopedia of the genes and metabolic pathways of H. influenzae. HinCyc connects the predicted genes, enzymes, enzyme-catalyzed reactions, and biochemical pathways in a WWW-accessible knowledge base to allow scientists to explore this complex hypothesis.",
crossref
= "PMID:8877511",
}
@Article{Karpetal00,
author
= "P. D. Karp and M. Riley
and M. Saier and I. T. Paulsen and S. M. Paley and A. Pellegrini-Toole",
title = "The EcoCyc and MetaCyc databases",
journal
= "Nucleic Acids
Research",
volume
= "28",
number
= "1",
pages
= "56--59",
year = "2000",
url = "http://nar.oupjournals.org/cgi/reprint/28/1/56.pdf",
keywords
= "metabolism, signaling,
EcoCyc, implementation, database, transport, knowledge representation, MetaCyc,
graphical, visualization, frames",
abstract
= "EcoCyc is an organism-specific
Pathway/Genome Database that describes the metabolic and signal-transduction
pathways of Escherichia coli, its enzymes, and-a new addition-its transport
proteins. MetaCyc is a new metabolic-pathway database that describes pathways
and enzymes of many different organisms, with a microbial focus. Both databases
are queried using the Pathway Tools graphical user interface, which provides a
wide variety of query operations and visualization tools. EcoCyc and MetaCyc
are available at http://ecocyc.PangeaSystems.com/ecocyc/",
crossref
= "PMID:10592180",
}
@InProceedings{KarpandPaleyl94,
author
= "P. D. Karp and S.
Paley",
title
= "Representations of
Metabolic Knowledge: Pathways",
booktitle =
"Intelligent Systems for
Molecular Biology",
volume
= "2",
pages
= "203—211",
year = "1994",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "http://www.ai.sri.com/pubs/papers/Karp94:Representations/document.ps.Z",
keywords
= "metabolism, knowledge
representation, implementation, database, EcoCyc, frames, inference,
graph",
abstract = "The automatic generation of drawings of metabolic pathways is a challenging problem that depends intimately on exactly what information has been recorded for each pathway, and on how that information is encoded. The chief contributions of the paper are a minimized representation for biochemical pathways called the predecessor list, and inference procedures for converting the predecessor list into a pathway-graph representation that can serve as input to a pathway-drawing algorithm. The predecessor list has several advantages over the pathway graph, including its compactness and its lack of redundancy. The conversion between the two representations can be formulated as both a constraint-satisfaction problem and a logical inference problem, whose goal is to assign directions to reactions, and to determine which are the main chemical compounds in the reaction. We describe a set of production rules that solves this inference problem. We also present heuristics for inferring whether the exterior compounds that are substrates of reactions at the periphery of a pathway are side or main compounds. These techniques were evaluated on 18 metabolic pathways from the EcoCyc knowledge base.",
crossref
= "PMID:7584392",
}
@InProceedings{KarpandRiley93,
author
= "P.D. Karp and M.
Riley",
title
= "Representations of
Metabolic Knowledge",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "1",
pages
= "207—215",
year = "1993",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "",
keywords
= "database, frames, knowledge
representation, metabolism, implementation, EcoCyc, comparative",
abstract = "Construction of electronic repositories of metabolic information is an increasingly active area of research. Encoding detailed knowledge of a complex biological domain requires finely honed representations. We survey representations used for several metabolic databases, including Eco-Cyc, and reach the following conclusions. Representation of the metabolism must distinguish enzyme classes from individual enzymes, because there is not a one-to-one mapping from enzymes to the reactions they catalyze. Individual enzymes must be represented explicitly as proteins, e.g., by encoding their subunit structure. The species variation of metabolism must be represented. So must the substrate specificity of enzymes, which may be treated in several ways.",
crossref
= "PMID:7584337",
}
@Article{KarpandMavrovouniotis,
author
= "P. Karp and M.
Mavrovouniotis",
title = "Representing, analyzing, and synthesizing biochemical
pathways",
journal
= "IEEE Expert",
volume = "9",
number
= "2",
pages
= "11--21",
year = "1994",
url = "http://www.ai.sri.com/pubs/papers/Karp94-11:Representing/document.ps.Z",
keywords
= "metabolism, knowledge
representation, database, simulation, pathway discovery, reconstruction,
inference, frames, analysis",
abstract
= "Living cells are complex
systems whose growth and existence depends on thousands of biochemical
reactions. A subset of these reactions -- the metabolism -- interconverts small molecules. A variety of
computational problems arise in representing knowledge of the metabolism in
electronic form, in analyzing that knowledge to gain deeper insights into
complexities of the metabolism, and in using such knowledge in biology,
biotechnology and health applications. These problems provide a rich set of
opportunities for exploiting existing AI techniques, and challenges for
developing new and improved techniques. This article describes challenges and
opportunities for addressing computational problems in the metabolism with
techniques from knowledge representation, planning, integration of
heterogeneous databases, qualitative reasoning, knowledge acquisition, and
machine learning. The computational problems include construction of large
shared knowledge bases of biochemical pathways, knowledge acquisition from the
biochemical literature, qualitative simulation of metabolic pathways,
thermodynamic estimation, synthesis of metabolic pathways, and scientific
hypothesis formation.",
crossref
= "",
}
@InProceedings{KarpandPaley94,
author
= "P. D. Karp and S. Paley
",
title
= "Automated Drawing of
Metabolic Pathways ",
booktitle
= "Proceedings of the third
international conference on bioinformatics and genome research ",
volume
= "",
pages
= "",
year = "1994",
editor
= "H. Lim and C. Cantor and
R. Robbins ",
publisher
= "",
address
= "",
url = "http://www.ai.sri.com/pubs/papers/Karp94:Automated/document.ps.Z",
keywords
= "EcoCyc, implementation,
visualoization, graph, knowledge representation, frames, metabolism,
database",
abstract = "The EcoCyc system consists of a knowledge base that describes the genes and intermediary metabolism of E. coli, and a graphical user interface (GUI) for accessing that knowledge. This paper presents algorithms for drawing metabolic pathways by dynamically querying the underlying knowledge base. These algorithms provide a foundation for building graphical user interfaces to metabolic databases. Pathway drawing is a graph-layout problem. Our algorithms draw pathways of several different topologies, including linear, cyclic, and branching pathways, as well as larger groupings of such pathways. The algorithms provide several visual presentations of metabolic pathways, for example, compounds can be drawn as names and/or chemical structures, and enzyme names and side compounds can be drawn or omitted. The GUI also provides several facilities for navigating in the space of biochemical pathways, such as traversing connections between pathways, and exploding or collapsing a pathway to include or exclude neighboring pathways.",
crossref
= "",
}
@Article{Karpetal99,
author
= "P. D. Karp and M. Krummenacker
and S. Paley and J. Wagg",
title
= "Integrated pathway/genome
databases and their role in drug discovery",
journal
= "Trends in
Biotechnology",
volume
= "17",
number
= "7",
pages
= "275--281",
year = "1999",
keywords
= "database, EcoCyc,
implementation, protein-protein, pathway discovery, visualization, comparative,
metabolism, inference, whole genome, frames",
abstract
= "Integrated pathway-genome
databases describe the genes and genome of an organism, as well as its
predicted pathways, reactions, enzymes and metabolites. In conjunction with
visualization and analysis software, these databases provide a framework for
improved understanding of microbial physiology and for antimicrobial drug
discovery. We describe pathway-based analyses of the genomes of a number of
medically relevant microorganisms and a novel software tool that visualizes
gene-expression data on a diagram showing the whole metabolic network of the
microorganism.",
crossref
= "PMID:10370234",
}
@InProceedings{KastenmullerandMewes99,
author
= "G. Kastenmuller and H. W. Mewes",
title
= "An ObjectOriented Data
Model for the Dynamic Modelling of Metabolic Pathways",
booktitle
= "Proceedings of the German
Conference on Bioinformatics (GCB'99)",
Series
= "",
volume
= "",
pages
= "",
year = "1999",
editor
= "R. Giegerich and R
Hofestadt and T. Lengauer and W. Mewes and D. Schomburg and M. Vingron and E.
Wingender ",
publisher
= "",
address
= "",
url = "http://www.bioinfo.de/isb/gcb99/poster/kastenmueller",
keywords
= "object-oriented, metabolism,
knowledge representation, ontology, database ",
abstract = "Modern techniques in molecular biology produce enormous amounts of biological data. Entire genomes have been sequenced, expression data for almost complete sets of genes of many organisms is now available. In order to cope with the data and to extract a maximal amount of information from it, sophisticated tools for the comprehensive and partly automatical analysis of the data have to be developed. As the focus shifts from genes to genomes, the analysis of metabolic pathways becomes important. Systems like KEGG [Ogata et al., 1999] provide a nearly complete but static view of the current knowledge in this field. A system for a dynamic modelling of metabolic pathways [Fellenberg and Mewes, 1999] would overcome many of the limitations of such static encyclopaedias. Here, we present an objectoriented data model for a pathway database. A system for dynamic modelling of metabolic pathways heavily relies on such a data model.",
crossref
= "",
}
@InProceedings{Kochetal99,
author
= "I. Koch and S. Schuster
and M. Heiner",
title
= "Simulation and analysis
of metabolic networks by timedependent Petri nets ",
booktitle
= "Proceedings of the German
Conference on Bioinformatics (GCB'99)",
Series
= "",
volume
= "",
pages = "",
year = "1999",
editor
= "R. Giegerich and R
Hofestadt and T. Lengauer and W. Mewes and D. Schomburg and M. Vingron and E.
Wingender",
publisher
= "",
address
= "",
url = "http://www.bioinfo.de/isb/gcb99/poster/koch",
keywords
= "Petri net, temporal,
metabolism, simulation, analysis, formal verification, discrete,
implementation, PED, hierarchical, PEDVisor, INA, deadlock, quantitative",
abstract = " Our poster describes the modeling, analysis, and simulation of the combined glycolytic and pentose phosphate pathway using timedependent Petri nets. The places represent biological compounds (metabolites) and the transitions chemical reactions between metabolites which are usually catalyzed by a certain enzyme. We extend the model proposed by Reddy et al. by taking also into account the reversible reactions and time dependencies. Stryer, 1996 suggests four main modes of the pentose phosphate pathway. We want to focus on the first mode for a detailed analysis. In this mode more ribose 5Âphosphate is required than NADPH, because rapidly dividing cells need ribose 5Âphosphate for the synthesis of nucleotide precursors of DNA. Following the glycolytic pathway most of the glucose 6phosphate is converted into fructose 6phosphate and glyceraldehyde 3phosphate phosphate, which are then converted by transaldolase and transketolase into ribose 5phosphate. We use a hierarchical Petri net for modeling this mode. The net was edited using the Petri net EDitor PED, which supports basically the construction of hierarchical place/transition nets with the specification of different types of places, transitions, and arcs, including their marking. The simulations of the nets were done using PEDVisor, which is not yet published. For the analysis of our model net we apply the program INA Integrated Net Analyzer. The used time dependencies are artificial. We assign to each transition a time interval to simulate a reaction rate. The first nonnegative number is the earliest firing time eft and the second the latest firing time lft. If the transition yields at time t¸ the concession to fire it can fire at the earliest at t + eft, and it must fire at the latest at t + lft. The time interval [0; 0] means that the transition will fire immediately. The resulting Petri net is structurally bounded and covered by semi positive Pinvariants. That means that there exists a vector describing a special marking, which always results in a constant by the scalar multiplication with any reachable state of the net. The net can reach 49 states. The minimal time is 21 units. The reachability graph is strongly connected and therefore the net is reversible. The net exhibits no time deadlocks and no dynamic conflicts. The net is live. Timedependent Petri nets exhibit a useful method for modeling and verification of metabolic pathways, for their timedependent and timeindependent analysis, and simulation of metabolic networks with and without disturbances. We think that our work is an initial step in this direction.",
crossref
= "",
}
@Article{KohnM92,
author
= "M. C. Kohn",
title = "Propagation of information in MetaNet graph
models",
journal
= "Journal of Theoretical
Biology",
volume
= "154",
number
= "4",
pages
= "505--517",g
year = "1992",
url = "http://valiant.niehs.nih.gov/MetaNet.html",
keywords
= "MetaNet, implementation,
metabolism, graph, algebraic, analysis, biochemistry",
abstract
= "Information flow in
metabolic networks has been studied with a graph model which represents the
biochemical transformations occurring in the system under investigation. The
"signal strength", an algebraic expression which estimates the
probability that an intermediate metabolite is bound to a given enzyme, has been
used to derive the "signal transmittance", the fraction of the
informational signal at one intermediate that reaches another intermediate. The
transmittance has been used to derive the "response ratio", the
sensitivity of the rate of change of information at one metabolite consequent
to a perturbation at another metabolite. Because the graphical representation
corresponds to the biochemical events presumed to occur in the network, these
quantities can be used to design experiments to confirm or falsify the hypotheses
underlying the model and aid in understanding the regulatory properties of the
system. The technique is illustrated by an example model, and its predictions
are shown to be sensitive to modest structural changes in the network.",
crossref
= "PMID:1593899",
}
@Article{KohnandLemieux91
author
= "M. C. Kohn and D. R.
Lemieux",
title = "Identification of regulatory properties of metabolic networks by graph theoretical modeling ",
journal
= "Journal of Theoretical Biology ",
volume
= "150",
number
= "1",
pages
= "3--25",
year = "1991",
url = "http://valiant.niehs.nih.gov/MetaNet.html",
keywords
= "graph, analysis, metabolism,
regulatory, protein-protein, feedback, quantitative",
abstract
= "An earlier graph theoretical
model of metabolic and gene-expression networks has been modified and extended
to include the effect of electrical potentials on binding constants,
representation of uncatalyzed processes, and treatment of parallel reactions
catalyzed by a single enzyme. Formal operations on the graph, which are
facilitated by a set of standardized guidelines, identify the feedback signals
in the network and rank them according to their influence. The technique was
applied to a model of glycolysis in ascites tumor cells in the absence and
presence of 12.5 mM exogenous glucose. Feedback regulation was widely
distributed and mostly due to binding of adenine nucleotide cofactors to the
enzymes of the network. The major changes in feedback regulation on adding
glucose is the relief of inhibition of hexokinase and phosphofructokinase and
the activation of pyruvate kinase. We conclude that regulation of tumor cell
glycolysis is not restricted to hexokinase or to (Na+,K+)-ATPase as was
previously suggested by others.",
crossref
= "PMID:1890846",
}
@InProceedings{KohnM98,
author
= "M. C. Kohn",
title
= "Identifying sites of
metabolic regulation by graph theoretical modeling",
booktitle
= "Modeling and Simulation of
Gene and Cell Regulation and Metabolic Pathways ",
Series
= "IBFI
Dagstuhl-Seminar-Report",
volume
= "215",
pages
= "",
year = "1998",
editor
= "J. Collades-Vides and R.
Hofestädt and M. Marvrovouniotis and G. Michal",
publisher
= "",
address
= "",
url = "http://wwwiti.cs.uni-magdeburg.de/iti_bm/dagstuhl/",
keywords
= "graph, analysis, metabolism,
regulatory, protein-protein, feedback, quantitative, implementation, MetaNet
",
abstract = "",
crossref
= "http://valiant.niehs.nih.gov/MetaNet.html",
}
@InProceedings{Kanneetal99,
author
= "C. C. Kanne and F.
Schreiber and D. Trumbach ",
title
= "Interactive Biochemical
Pathways",
booktitle
= "Proceedings of the German
Conference on Bioinformatics (GCB'99)",
volume
= "",
pages
= "204--205",
year = "1999",
editor
= "",
publisher
= "",
address
= "Hannover",
url = "",
keywords
= "database, Electronic Biochemical
Pathways, implementation, visualization, comparative, spatial,
object-oriented",
abstract = "This project deals with the visual representation of biochemical information. Important aspects are the representation of arbitrary parts of pathways, the comparison of biochemical reactions in different organisms, the view of regulative processes, and the consideration of compartments. The results of the database queries are mostly pathways. These are visualized by a drawing algorithm. An automatic drawing is necessary here because the retrieved pathways are arbitrary subsets of the database, and one can therefore not rely on having a drawing for this very pathway. Also, this technique allows to reflect changes in the database immediately. The pathways can be annotated with selected additional information, such as structural formulas, regulative processes or compartmentation. This is neccessary to accommodate to different types of users, such as researchers, students or doctors. Arranging parts of pathways into single objects enhance the readability of the obtained diagrams.",
crossref
=
"http://www.fmi.uni-passau.de/Graphlet/",
}
@InProceedings{Kanneetal99a,
author
= "C. C. Kanne and F.
Schreiber and D. Trumbach ",
title
= "Electronic Biochemical
Pathways",
booktitle
= "Proceedings of the 7th
international Symposium on Graph Drawing (GD '99)",
Series
= "Lecture Notes in Computer
Science",
volume
= "1731",
pages
= "418--419",
year = "1999",
editor
= "",
publisher
= "Springer Verlag",
address
= "",
keywords
= "database, Electronic
Biochemical Pathways, implementation, visualization, comparative, spatial,
object-oriented, biochemistry, UML, markup, comparative, pathway alignment,
graph, graphical",
abstract = "The biochemistry of living beings is a complex network of reactants, products and enzymes with multiple interconnections representing reactions and regulation. Examples are given by the Boehringer poster and the atlas "Biochemical Pathways". In the Electronic Biochemical Pathways project we intend to build a platform for a convenient electronic access to the information covered by the poster and the atlas. The Electronic Biochemical Pathways has three major parts. First, chemical information is modeled accurately and in detail. This data is stored in a database which also contains explicit connections between the different subjects (for example, showing the diseases related to a certain reaction pathway). Using this database and advanced automatic visualization of the involved reaction graphs, the resulting software system will provide users with new ways of considering and analyzing metabolic pathways. The project is divided into three parts: Acquiring and modeling the data, the suitable database environment, and the graph visualization system. ",
crossref
=
"www.biochemical-pathways.de",
}
@Article{KlippandHeinrich99,
author
= "E. Klipp and R.
Heinrich",
title = "Competition for enzymes in metabolic pathways:
implications for optimal distributions of enzyme concentrations and for the
distribution of flux control",
journal
= "Biosystems",
volume
= "54",
number
= "1--2",
pages
= "1--14",
year = "1999",
url = "",
keywords
= "metabolism, kinetic,
analysis, biochemistry, steady state, flux balancing, metabolic control,
optimization, quantitative",
abstract = "The structures of biochemical pathways are assumed to be determined by evolutionary optimization processes. In the framework of mathematical models, these structures should be explained by the formulation of optimization principles. In the present work, the principle of minimal total enzyme concentration at fixed steady state fluxes is applied to metabolic networks. According to this principle there exists a competition of the reactions for the available amount of enzymes such that all biological functions are maintained. In states which fulfill these optimization criteria the enzyme concentrations are distributed in a non-uniform manner among the reactions. This result has consequences for the distribution of flux control. It is shown that the flux control matrix c, the elasticity matrix epsilon, and the vector e of enzyme concentrations fulfill in optimal states the relations c(T)e = e and epsilon(T)e=0. Starting from a well-balanced distribution of enzymes the minimization of total enzyme concentration leads to a lowering of the SD of the flux control coefficients.",
crossref
= "PMID:10658833",
}
@Article{Kuffneretal00,
author
= "R. Kuffner and R. Zimmer
and T. Lengauer",
title
= "Pathway analysis in
metabolic databases via differential metabolic display",
journal
= "Bioinformatics",
volume
= "16",
number
= "9",
pages
= "825--836",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/9/825.pdf",
keywords
= "Petri net, metabolism,
pathway discovery, implementation, ToPLign, database, differential metabolic
display, regulatory, comparative, score",
abstract
= "Motivation: A number of
metabolic databases are available electronically, some with features for
querying and visualizing metabolic pathways and regulatory networks. We present
a unifying, systematic approach based on PETRI nets for storing, displaying,
comparing, searching and simulating such nets from a number of different
sources. Results: Information from each data source is extracted and compiled
into a PETRI net. Such PETRI nets then allow to investigate the (differential)
content in metabolic databases, to map and integrate genomic information and
functional annotations, to compare sequence and metabolic databases with
respect to their functional annotations, and to define, generate and search
paths and pathways in nets. We present an algorithm to systematically generate
all pathways satisfying additional constraints in such PETRI nets. Finally,
based on the set of valid pathways, so-called differential metabolic displays
(DMDs) are introduced to exhibit specific differences between biological
systems, i.e. different developmental states, disease states, or different
organisms, on the level of paths and pathways. DMDs will be useful for target
finding and function prediction, especially in the context of the interpretation
of expression data. Availability: Part of this work has been integrated into
the software package ToPLign available for use over the WWW at
http://cartan.gmd.de/ToPLign.html.",
crossref
= "PMID:11108705",
}
@InProceedings{Kozaetal01,
author
= "J.R. Koza and W. Mydlowec
and G. Lanza and J. Yu and M.A. Keane",
title
= "Reverse Engineering of
Metabolic Pathways from Observed Data Using Genetic Programming",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "6",
pages
= "434--445",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/koza.pdf",
keywords
= "reconstruction, circuit,
SPICE, implementation, kinetic, program tree, simulation, comparative, score,
metabolism, genetic programming ",
abstract
= "Recent work has demonstrated
that genetic programming is capable of automatically creating complex networks
(such as analog electrical circuits and controllers) whose behavior is modeled
by linear and non-linear continuous-time differential equations and whose
behavior matches pre-specified output values. The concentrations of substances
participating in networks of chemical reactions are also modeled by non-linear
continuous-time differential equations. This paper demonstrates that it is
possible to automatically create (reverse engineer) a network of chemical
reactions from observed time-domain data. Genetic programming starts with
observed time-domain concentrations of input substances and automatically
creates both the topology of the network of chemical reactions and the rates of
each reaction within the network such that the concentration of the final
product of the automatically created network matches the observed time-domain
data. Specifically, genetic programming automatically created metabolic
pathways involved in the phospholipid cycle and the synthesis and degradation
of ketone bodies.",
crossref
= "",
}
@TechReport{Kozaetal00,
author = "J. R. Koza, W. Mydlowec, G.
Lanza, J. Yu, & M. A. Keane",
title = "Reverse Engineering and
Automatic Synthesis of Metabolic Pathways from Observed Data Using Genetic
Programming",
institution = "Stanford
University",
year = "2000",
month = "",
note = "SMI technical report
SMI-2000-0851",
url = "http://www-smi.stanford.edu/pubs/SMI_Reports/SMI-2000-0851.pdf",
keywords
= "reconstruction, circuit,
SPICE, implementation, kinetic, program tree, simulation, comparative, score,
metabolism, genetic programming",
abstract
= "Recent work has demonstrated
that genetic programming is capable of automatically creating complex networks
(such as analog electrical circuits and controllers) whose behavior is modeled
by continuous-time differential equations (both linear and non-linear) and
whose behavior matches prespecified output values. The concentrations of
substances participating in networks of chemical reactions are also modeled by
non-linear continuous-time differential equations. This paper demonstrates that
it is possible to automatically create (reverse engineer) a network of chemical
reactions from observed time-domain data. Genetic programming starts with
observed time-domain concentrations of input substances and automatically
creates both the topology of the network of chemical reactions and the rates of
each reaction within the network such that the concentration of the final
product of the automatically created network matches the observed time-domain
data. This paper describes how genetic programming automatically created a
metabolic pathway involving four chemical reactions that takes in glycerol and
fatty acid as input, uses ATP as a cofactor, and produces diacyl-glycerol as
its final product. In addition, this paper describes how genetic programming
similarly created a metabolic pathway involving three chemical reactions for
the synthesis and degradation of ketone bodies. Both automatically created
metabolic pathways contain at least one instance of three noteworthy
topological features, namely an internal feedback loop, a bifurcation point
where one substance is distributed to two different reactions, and an accumulation
point where one substance is accumulated from two sources.",
crossref
= "",
}
@Article{Kolpakovetal98,
author
= "F. A. Kolpakov and E. A.
Ananko and G. B. Kolesov and N. A. Kolchanov",
title
= "GeneNet: a gene network database and its automated
visualization",
journal
= "Bioinformatics",
volume
= "14",
number
= "8",
pages
= "529--537",
year = "1998",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/14/6/529.pdf",
keywords
= "visualization, GeNet,
implementation, database, object-oriented, kinetic, graphical, regulatory,
biochemistry, signaling, equivalence",
abstract
= "MOTIVATION: Gene networks
that provide the regulation of physiological processes are the basic feature of
organisms. Information regarding the regulation of gene expression and signal
transduction pathways is increasing rapidly. However, the information is hard
to formalize and systematize. Ways and means for automated visualization of the
gene networks based on their formalized description are needed. RESULTS: The
object-oriented database GeneNet and the software for its automated
visualization have been developed. The main principles of a formalized
description of the gene network have been worked out. Antiviral response and
erythropoiesis are provided as examples to show how this is achieved. The
GeneNet graphical user interface written in Java provides automated generation
of the gene network diagrams and allows visualization and exploration of the
GeneNet database through the Internet. A system of filters allows the selection
of particular components of the network for visualization. AVAILABILITY: The
GeneNet database and its graphical user interface are available at
http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneNet/",
crossref
= "PMID:9694992",
}
@Article{KolpakovandAnankol99,
author
= "F. A. Kolpakov and E. A.
Ananko",
title
= "Interactive data input
into the GeneNet database",
journal
= "Bioinformatics",
volume
= "15",
number
= "7--8",
pages
= "713--714",
year = "1999",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/15/7/713.pdf",
keywords
= "visualization, GeNet,
implementation, database, object-oriented, kinetic, graphical, regulatory,
biochemistry, signaling, equivalence",
abstract
= "SUMMARY: The GeneNet
database has been developed for a formalized hierarchical description of the
gene networks. To provide rapid data accumulation in the database, the Java
graphical interface for data input through the Internet by independent experts
equipped with convenient visual tools is developed. AVAILABILITY:
http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneNet/",
crossref
= "PMID:10487877",
}
@InProceedings{Kyodaetal00,
author
= "K.M. Kyoda and M. Muraki
and H. Kitano",
title
= "Construction of a
generalized simulator for multi-cellular organisms and its application to SMAD
signal transduction",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "5",
pages
= "317--328",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/kyoda.pdf",
keywords
= "kinetic, continuous,
signaling, simulation, multicellular, spatial, implementation",
abstract
= "In this paper, we report
development of a generalized simulation system based on ordinary differential
equations for multi-cellular organisms, and results of the analysis on a Smad
signal transduction cascade. The simulator implements intra-cellular and
extra-cellular molecular processes, such as protein diffusion, ligand-receptor
reaction, biochemical reaction, and gene expression. It simulates the
spatio-temporal patterning in various biological phenomena for the single and
multi-cellular organisms. In order to demonstrate the usefulness of the
simulator, we constructed a model of Drosophila's Smad signal transduction,
which includes protein diffusion, biochemical reaction and gene expression. The
results suggest that the presence of negative feedback mechanism in the Smad
pathway functions to improve the frequency response of the cascade against
changes in the signaling.",
crossref
= "PMID:10902180",
}
@InProceedings{KyodaandKatano99,
author
= "K.M. Kyoda and H.
Kitano",
title
= "Simulation of genetic
interaction for Drosophila leg formation",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "77--89",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Kyoda.pdf",
keywords
= "kinetic, stochastic,
regulatory, simulation, multicellular, signaling",
abstract
= "The formation of Drosophila
wings and legs are major research topics in Drosophila development, and several
hypotheses, such as the polar-coordinate model and the boundary model, has been
proposed to explain mechanisms behind these phenomena. A series of recent
studies have revealed complex interaction among genes involved in establishing
three principal axes (A-P, D-V, and P-D) of leg formation. In this paper, we
present a simulation system for leg formation, simulating the genes
interactions involved. We use this simulator to investigate a mathematical
framework of leg formation which is otherwise well-founded from a molecular
perspective. Particularly, we focus on the formation of the expression patterns
of dpp, wg, dll, dac, al, en, hh and ci genes, which are involved in the
development of the third instar Drosophila leg disc. The most interesting part
of this research is showing how the coaxial gene expression patterns behind the
P-D axis can be formed, and how positional information, as postulated in the
polar-coordinate model, can be conveyed to each cell. Our results suggest that
P-D axis can be formed by a set of genes with different activation thresholds;
the process involves different chemical gradients of dpp and wg products,
forming a bi-polar contour. Interestingly, this combination of chemical
gradients can specify unique positions of cells for the hemisphere, leaving the
A-P axis determiner to decide only whether the cells are anterior or posterior.
All in all, our so-called Bi-Polar Model describes axial formation of the leg
disc well.",
crossref
= "PMID:10380187",
}
@Article{Kohn99,
author
= "K. W. Kohn",
title
= "Molecular Interaction Map
of the Mammalian Cell Cycle Control and DNA Repair Systems",
journal
= "Molecular Biology of the Cell",
year = "1999",
volume
= "10",
number
= "",
pages
= "2703--2734",
url = "http://www.pubmedcentral.nih.gov/picrender.cgi?artid=1041&pictype=5",
keywords
= "graphical, biochemistry,
regulatory, visulaization, circuit, interaction map, knowledge
representation",
abstract
= "Eventually to understand the
integrated function of the cell cycle regulatory network, we must organize the
known interactions in the form of a diagram, map, and/or database. A diagram
convention was designed capable of unambiguous representation of networks
containing multiprotein complexes, protein modifications, and enzymes that are
substrates of other enzymes. To facilitate linkage to a database, each
molecular species is symbolically represented only once in each diagram.
Molecular species can be located on the map by means of indexed grid
coordinates. Each interaction is referenced to an annotation list where
pertinent information and references can be found. Parts of the network are
grouped into functional subsystems. The map shows how multiprotein complexes
could assemble and function at gene promoter sites and at sites of DNA damage.
It also portrays the richness of connections between the p53-Mdm2 subsystem and
other parts of the network.",
crossref
= "PMID:10436023",
}
@Article{Kohn98,
author
= "K. W. Kohn",
title
= "Functional capabilities
of molecular network components controlling the mammalian G1/S cell cycle phase
transition.",
journal
= "Oncogene",
year = "1998",
volume
= "16",
number
= "",
pages
= "1065--1075",
url = "http://www.stockton-press.co.uk/server-java/Arknoid/stockton_pri/0950-9232/v16n8/pdf/1201608a.pdf",
keywords
= "graphical, biochemistry,
regulatory, visulaization, circuit, interaction map, knowledge representation,
simulation",
abstract
= "The molecular interactions
implicated in the mammalian G1/S cell cycle phase transition comprise a highly
nonlinear network which can produce seemingly paradoxical results and make
intuitive interpretations unreliable. A new approach to this problem is
presented, consisting of (1) a convention of unambiguous reaction diagrams, (2)
a convenient computer simulation method, and (3) a quasi-evolutionary method of
probing the functional capabilities of simplified components of the network.
Simulations were carried out for a sequence of hypothetical primordial systems,
beginning with the simplest plausibly functional system. The complexity of the
system was then increased in small steps, such that functionality was added at
each step. The results suggested new functional concepts: (1) Rb-family
proteins could store E2F in a manner analogous to the way a condenser stores
electric charge, and, upon phosphorylation, release a large wave of active E2F;
(2) excessive or premature cyclin-dependent kinase activities could
paradoxically impair E2F activity during the G1/S transition period. The
results show how network simulations, carried out by means of the methods
described, can assist in the design and interpretation of experiments probing
the control of the G1/S phase transition.",
crossref
= "PMID:9519880",
}
@PhDThesis{Kam00,
author = "N. Kam",
title = "The Immune System as a Reactive System: Modeling T Cell
Activation Using Statecharts",
school = "Weizmann Institute of
Science",
year = "2000",
month = "July",
url = "",
keywords
= "Statecharts, graphical,
implementation, immune, Rhaphsody, semi-quantitative, visualization,
object-oriented, formal verification",
abstract
= "The construction of reliable
reactive systems is considered to be one of the most challenging activities in
the fields of software and system engineering. Unlike transformational systems,
whose role is to produce a final result at the end of a terminating
computation, the role of reactive systems is to maintain some ongoing
interaction with their environment.This implies that reactive systems cannot be
specified by a relation between an initial and a final state, but rather by
describing their ongoing behavior. Trying to cope with this challenge, a visual
language called statecharts was developed for specifiying and designing large and
complex reactive systems. The definition of a reactive system definitely suits
biological systems at different levels, ranging from a genetic network to a
developing embryo or the immune systems of an adult. Various mathematical
approaches have been used for describing different aspects of immune activity.
However, as far as we know, this is the first attempt at analyzing the immune
system (or any other biological system) as a reactive system, therefore
applying special tools (developed for constructing non-existing computerized
systems) to model the immune system. Statecharts, within the framework of the
object-oriented modeling approach, seem to fulfill the basic requirements
desired of a modeling language to be used for modeling biological systems in a
bottom-up approach. The results described here indicate that this modeling
strategy might contribute to the transition of biology from the phase of
analysis to the phase of synthesis.",
}
@Article{KoikeandRzhetsky00,
author
= "T. Koike and A.
Rzhetsky",
title
= "A Graphic Editor for
Analyzing Signal Transduction Pathways",
journal
= "Gene",
year = "2000",
volume
= "",
number
= "",
pages
= "",
note = "in press",
url = "http://genome6.cpmc.columbia.edu/andrey/TomohiroGene.pdf",
keywords
= "Visualization, regulatory,
java, signaling, logic, biochemistry, Cutenet, ontology, implementation",
abstract
= "We describe a graphical
editor designed specifically to facilitate analysis and visualization of
complex signal-transduction pathways. The editor provides automatic layout of
complex regulatory graphs and enables users easily to maintain, edit, and
exchange publication-quality images of regulatory networks.",
crossref
= "PMID:11163981",
}
@Article{Karp00,
author
= "P. D. Karp",
title
= "An ontology for
biological function based on molecular interactions",
journal
= "Bioinformatics",
year = "2000",
volume
= "16",
number
= "3",
pages
= "269--285",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/3/269.pdf",
keywords
= "ontology, knowledge
representation, protein-protein, database, implementation, EcoCyc, metabolism,
signaling, regulatory, frames",
abstract = "MOTIVATIONS: A number of important
bioinformatics computations involve computing with function: executing
computational operations whose inputs or outputs are descriptions of the
functions of biomolecules. Examples include performing functional queries to
sequence and pathway databases, and determining functional equality to evaluate
algorithms that predict function from sequence. A prerequisite to computing
with function is the existence of an ontology that provides a structured
semantic encoding of function. Functional bioinformatics is an emerging
subfield of bioinformatics that is concerned with developing ontologies and
algorithms for computing with biological function. RESULTS: The article
explores the notion of computing with function, and explains the importance of
ontologies of function to bioinformatics. The functional ontology developed for
the EcoCyc database is presented. This ontology can encode a diverse array of
biochemical processes, including enzymatic reactions involving small-molecule
substrates and macromolecular substrates, signal-transduction processes,
transport events, and mechanisms of regulation of gene expression. The ontology
is validated through its use to express complex functional queries for the
EcoCyc DB.",
crossref = "PMID:10869020",
}
@InCollection{Kazic94,
author
= "T. Kazic",
editor
= "T. Kumosinksi and M. N.
Liebman",
booktitle
= "Molecular Modeling: From
Virtual Tools to Real Problems",
title = "Representation of Biochemistry for Modeling Organisms",
publisher
= "American Chemical
Society",
address
= "Washington, DC",
pages
= "486--494",
year = "1994",
url = "http://www.ibc.wustl.edu/papers/moirai/acs.ps",
keywords =
"logic, biochemistry, prolog, quantitative",
abstract
= "Before one makes a database,
one must needs understand the fundmntal structure of that portion of the ``real
world'' the database is intended to model. This understanding inevitably guides
decisions on representation and implementation, so its fidelity to reality is
critical: an accurate model is easier to change as knowledge evolves, and
appropriate representational choices simplify the process of database revision.
In this paper I describe the basic representational principles we have reached
in our attempt to model portions of cellular biochemistry, and sketch some of
their consequences for representation and our implementations.",
crossref
= "",
}
@Article{Kazic00,
author
= "T. Kazic",
title
= "Semiotes: a Semantics for
Sharing",
journal
= "Bioinformatics",
year = "2000",
volume
= "16",
number
= "12",
pages
= "1129--1144",
note = "",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/12/1129.pdf",
keywords = "logic, biochemistry, prolog,
semantics, metadata, ontology, knowledge representation, database, executable,
exchange, qualitative",
abstract
= "Reliable, automated
communication of biological information requires methods to declare the
information's semantics. In this paper I describe an approach to semantic
declaration intended to permit independent, distributed databases, algorithms,
and servers to exchange and process requests for information and computations
without requiring coordination or agreement among them on universe of
discourse, data model, schema, or implementation. This approach uses Glossa, a
formal language defining the semantics of biological ideas, information, and
algorithms, to executably define the semantics of complex ideas and
computations by constructs of semiotes, terms which axiomatically define very
simple notions. A database or algorithm wishing to exchange information or
computations maintains a set of mappings between its particular notions and
semiotes, and a parser to translate between its indigenous ideas and
implementation and the semiotes. Requests from other databases or algorithms
are issued as semiotic messages, locally interpreted and processed, and the
results returned as semiotes to the requesting entity. Thus, semiotes serve as
a shared, abstract layer of definitions which can be computably combined by
each database or algorithm according to its own needs and ideas. By combining
the explicit declaration of semantics with the computation of the semantics of complex
ideas, Glossa and its semiotes permit independent computational entities to
lightly federate their capabilities as desired while maintaining their unique
perspectives on both scientific and technical questions. ",
crossref
= "PMID:11159332",
}
@InProceedings{KazicTsur93,
author
= "T. Kazic and S.
Tsur",
title
= "Modeling and Simulating
Biological Processes as Logical Enterprises",
booktitle
= "Proceedings of the NSF Scientific
Database Projects, 1991-1993",
pages
= "16--22",
year = "1993",
editor
= "W. W. Chu and A. F.
Cardenas and R. K. Taira",
publisher
= "National Science
Foundation",
address
= "Washington, DC",
url = "http://www.ibc.wustl.edu/papers/moirai/nsf_report93.ps",
keywords
= "logic, declarative,
biochemistry, executable, database,quantitative",
abstract
= "Understanding and improving
the biological machines responsible for very complex phenomena would be greatly
speeded by a computational tool which simulates the outcome of laboratory
manipulations. These processes are extremely diOEcult to think about because
they involve literally hundreds of interacting parts. For modeling to be
realistic enough to be useful, the model must include detailed information on
both the structure of the molecular parts and their functions in biochemical
reactions. Representing and using this information in databases to simulate
even simple processes is the ørst step to achieving larger, more comprehensive
models. We are studying how the molecules, reactions and constraints on their
interactions can be represented in the computer. A key requirement is that
facts, ideas and questions all be represented in the same language and using
the same fundamental approach, while still permitting scientists to describe
and manipulate ideas in the language they find most natural. We have achieved
this goal by using declarative database technology and by expressing molecules,
reactions and constraints in a formal grammar. The grammar allows one to pick
the most congenial way to describe and model the biochemistry in a detailed and
comprehensive manner. ",
}
@TechReport{Kazicetal00,
author = "T. Kazic and A. Bugrim and B.
Dunford-Shore and B. Feng and F. Fabrizio and J. Holcomb and J. Slomczynski and
W. B. Wise",
title = "Moirai: toward the Simulation
of Cellular Systems",
institution = "Washington
University",
year = "2000",
month = "February",
note = "IBC technical report",
url = "http://www.ibc.wustl.edu/papers/moirai/tech3.ps",
keywords
= "logic, biochemistry, graph,
declarative, database, simulation, structure, implementation, Moirai",
abstract
= "Organisms and their
components form complex, intricate systems which maintain stability,
robustness, and flexibility in the face of genetic, environmental, and
evolutionary changes. How these properties are achieved is unknown, though
obviously the organization of these systems is critical to these functions.
Modelling such systems computationally will be among the most important methods
in their elucidation; but until recently there has been very little
intellectual or technical infrastructure for modelling large, intricately
structured networks of biochemical reactions in appropriate molecular detail.
In this paper we describe the progress we have made toward that infrastructure,
giving the motivating rationale, the key theoretical foundations, and a brief
description of the implemented components of Moirai.",
}
L
@Article{LeNovereandShimizu01,
author
= "N. Le Novere and T. S.
Shimizu",
title = "STOCHSIM: modelling of stochastic biomolecular processes",
journal
= "Bioinformatics",
volume
= "17",
number = "6",
pages
= "575--576",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/6/575.pdf",
keywords
= "stochastic, quantitative,
implementation, StochSim, simulation, object-oriented, quantitative, molecular,
biochemistry, spatial",
abstract
= "SUMMARY: STOCHSIM is a
stochastic simulator for chemical reactions. Molecules are represented as
individual software objects that react according to probabilities derived from
concentrations and rate constants. Version 1.2 of STOCHSIM provides a novel
cross-platform graphical interface written in Perl/Tk. A simple two-dimensional
spatial structure has also been implemented, in which nearest-neighbour
interactions of molecules in a 2-D lattice can be simulated.",
crossref
= "PMID:11395441",
}
@InProceedings{Liangetal98,
author
= "S. Liang and S. Fuhrman
and R. Somogyi",
title
= "Reveal, a general reverse
engineering algorithm for inference of genetic network architectures",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "18--29",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/liang.pdf",
keywords
= "Boolean network,
synchronous, reconstruction, REVEAL, implementation, regulatory",
abstract
= "Given the immanent gene
expression mapping covering whole genomes during development, health and
disease, we seek computational methods to maximize functional inference from
such large data sets. Is it possible, in principle, to completely infer a
complex regulatory network architecture from input/output patterns of its
variables? We investigated this possibility using binary models of genetic
networks. Trajectories, or state transition tables of Boolean nets, resemble
time series of gene expression. By systematically analyzing the mutual
information between input states and output states, one is able to infer the
sets of input elements controlling each element or gene in the network. This
process is unequivocal and exact for complete state transition tables. We
implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and
found the problem to be tractable within the conditions tested so far. For n =
50 (elements) and k = 3 (inputs per element), the analysis of incomplete state
transition tables (100 state transition pairs out of a possible 10(15))
reliably produced the original rule and wiring sets. While this study is
limited to synchronous Boolean networks, the algorithm is generalizable to
include multi-state models, essentially allowing direct application to
realistic biological data sets. The ability to adequately solve the inverse
problem may enable in-depth analysis of complex dynamic systems in biology and
other fields.",
crossref
= "PMID:9697168",
}
@Article{Marcotteetal01,
author
= "E. M.
Marcotte and I. Xenarios and D. Eisenberg",
title = "Mining literature for protein-protein interactions",
journal
= "Bioinformatics",
volume
= "17",
number
= "4",
pages
= "359--363",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/4/359.pdf",
keywords
= "protein-protein, information
extraction, literature, qualitative, implementation, DIP",
abstract
= "MOTIVATION:
A central problem in bioinformatics is how to capture information from the vast
current scientific literature in a form suitable for analysis by computer. We
address the special case of information on protein-protein interactions, and
show that the frequencies of words in Medline abstracts can be used to
determine whether or not a given paper discusses protein-protein interactions.
For those papers determined to discuss this topic, the relevant information can
be captured for the Database of Interacting PROTEINS: Furthermore, suitable
gene annotations can also be captured. RESULTS: Our Bayesian approach scores
Medline abstracts for probability of discussing the topic of interest according
to the frequencies of discriminating words found in the abstract. More than 80
discriminating words (e.g. complex, interaction, two-hybrid) were determined
from a training set of 260 Medline abstracts corresponding to previously
validated entries in the Database of Interacting Proteins. Using these words
and a log likelihood scoring function, approximately 2000 Medline abstracts
were identified as describing interactions between yeast proteins. This
approach now forms the basis for the rapid expansion of the Database of
Interacting Proteins.",
crossref
= "PMID:11301305",
}
@Article{MendesandKell01,
author
= "P. Mendes and D. B.
Kell",
title = "MEG (Model Extender for Gepasi): a program for the modelling of complex, heterogeneous, cellular systems",
journal
= "Bioinformatics",
volume
= "17",
number
= "3",
pages
= "288--289",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/3/288.pdf",
keywords
= "implementation, metabolism,
biochemistry, quantitative, spatial, simulation, MEG, Gepasi, multicellular,
kinetic",
abstract
= "SUMMARY: We describe a
program for the construction of spatially distributed metabolic models, which
may then be simulated using the metabolic simulator GEPASI: This is useful for
the modelling of heterogeneous systems whether as liquid cultures or as
spatially organised systems with specified interconnections.",
crossref
= "PMID:11294797",
}
@Article{Mrowka01,
author
= "R. Mrowka",
title = "A Java applet for visualizing protein-protein interaction ",
journal
= "Bioinformatics",
volume
= "17",
number
= "7",
pages
= "669--671",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/7/669.pdf",
keywords = "protein-protein, implementation, graphical, visualization, graph, qualitative, java, whole genome",
abstract
= "Summary:
A web applet for browsing protein-protein interactions was implemented. It
enables the display of interaction relationships, based upon neighboring
distance and biological function. Availability: The Java applet is available at
http://www.charite.de/bioinformatics",
crossref
= "PMID:11448890",
}
@Article{Marcotteetal99a,
author = "E. M. Marcotte and M. Pellegrini and H. L. Ng and D. W. Rice and T. O. Yeates and D. Eisenberg",
title = "Detecting protein function and protein-protein interactions from genome sequences ",
journal
= "Science",
volume
= "285",
number
= "5428",
pages
= "751--753",
year = "1999",
url = "http://www.sciencemag.org/cgi/reprint/285/5428/751.pdf",
keywords
= "reconstruction, analysis,
whole genome, domain, protein-protein, metabolism, interaction map, DIP,
implementation, database, Rosetta stone",
abstract
= "A computational method is
proposed for inferring protein interactions from genome sequences on the basis
of the observation that some pairs of interacting proteins have homologs in
another organism fused into a single protein chain. Searching sequences from
many genomes revealed 6809 such putative protein-protein interactions in
Escherichia coli and 45,502 in yeast. Many members of these pairs were
confirmed as functionally related; computational filtering further enriches for
interactions. Some proteins have links to several other proteins; these coupled
links appear to represent functional interactions such as complexes or
pathways. Experimentally confirmed interacting pairs are documented in a
Database of Interacting Proteins.",
crossref
= "PMID:10427000",
}
@Article{Marcotteetal99,
author
= "E. M. Marcotte and M.
Pellegrini and M. J. Thompson and T. O. Yeates and D. Eisenberg",
title = "A combined algorithm for genome-wide prediction of
protein function ",
journal
= "Nature",
volume
= "402",
number
= "6757",
pages
= "83--86",
year = "1999",
keywords
= "reconstruction,
protein-protein, metabolism, comparative, phylogenetic profile, domain, interaction
map, graph, analysis, whole genome, qualitative, pathway discovery, Rosetta
stone",
abstract
= "The availability of over 20
fully sequenced genomes has driven the development of new methods to find
protein function and interactions. Here we group proteins by correlated
evolution, correlated messenger RNA expression patterns and patterns of domain
fusion to determine functional relationships among the 6,217 proteins of the
yeast Saccharomyces cerevisiae. Using these methods, we discover over 93,000
pairwise links between functionally related yeast proteins. Links between
characterized and uncharacterized proteins allow a general function to be
assigned to more than half of the 2,557 previously uncharacterized yeast
proteins. Examples of functional links are given for a protein family of
previously unknown function, a protein whose human homologues are implicated in
colon cancer and the yeast prion Sup35.",
crossref
= "PMID:10573421",
}
@Article{MendesandKell98,
author
= "P. Mendes and D.
Kell",
title = "Non-linear optimization of biochemical pathways:
applications to metabolic engineering and parameter estimation",
journal
= "Bioinformatics",
volume
= "14",
number
= "10",
pages
= "869--883",
year = "1998",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/14/10/869.pdf
keywords
= "implementation, Gepasi, analysis, metabolism, kinetic,
quantitative, optimization, non-linear, simulation, engineering,
reconstruction",
abstract
= "MOTIVATION: The simulation
of biochemical kinetic systems is a powerful approach that can be used for: (i)
checking the consistency of a postulated model with a set of experimental
measurements, (ii) answering 'what if?' questions and (iii) exploring possible
behaviours of a model. Here we describe a generic approach to combine numerical
optimization methods with biochemical kinetic simulations, which is suitable
for use in the rational design of improved metabolic pathways with industrial
significance (metabolic engineering) and for solving the inverse problem of
metabolic pathways, i.e. the estimation of parameters from measured variables.
RESULTS: We discuss the suitability of various optimization methods, focusing
especially on their ability or otherwise to find global optima. We recommend
that a suite of diverse optimization methods should be available in simulation
software as no single one performs best for all problems. We describe how we
have implemented such a simulation-optimization strategy in the biochemical
kinetics simulator Gepasi and present examples of its application.
AVAILABILITY: The new version of Gepasi (3.20), incorporating the methodology
described here, is available on the Internet at
http://gepasi.dbs.aber.ac.uk/softw/Gepasi.",
crossref
= "PMID:9927716",
}
@PhDThesis{Mendes94,
author = "P. Mendes",
title = "Computer simulation of the
dynamics of biochemical pathways",
school = "University of Wales,
Aberystwyth",
year = "1994",
month = "",
url = "ftp://gepasi.dbs.aber.ac.uk/pedro/",
keywords
= "implementation, Gepasi,
analysis, metabolism, kinetic, quantitative, optimization, non-linear,
simulation, engineering, reconstruction",
abstract
= "",
crossref
= "",
}
@Article{Mendes93,
author
= "P. Mendes",
title = "GEPASI: a software package for modelling the dynamics, steady states and control of biochemical and other systems ",
journal
= "Computational Applied
Bioscience",
volume
= "9",
number
= "5",
pages
= "563--571",
year = "1993",
url = "",
keywords
= "Gepasi, implementation, simulation,
metabolism, steady state, analysis, metabolic control, systemic, numerical,
quantitative, kinetic ",
abstract
= "GEPASI is a software system
for modelling chemical and biochemical reaction networks on computers running
Microsoft Windows. For any system of up to 45 metabolites and 45 reactions,
each with any user-defined or one of 35 predefined rate equations, one can
produce trajectories of the metabolite concentrations and obtain a steady state
(if it does exist). When steady-state solutions are produced, elasticity and
control coefficients, as defined in metabolic control analysis, are calculated.
GEPASI also allows the automatic generation of a sequence of simulations with
different combinations of parameter values, effectively scanning a hyper-solid
in parameter space. Together with the ability to produce user-defined columnar
data files, these features allow for both very quick and systematic study of
biochemical pathway models. The source code (in C) is available on request from
the author, and while the user interface is dependent on having MS-Windows as
the operating system, the numerical part is portable to other operating
systems. GEPASI is suitable both for research and educational purposes.
Although GEPASI was written with biochemical pathways in mind, it can equally
be used to stimulate other dynamical systems.",
crossref
= "PMID:8293329",
}
@Article{Michal98,
author
= "G. Michal",
title = "On representation of metabolic pathways",
journal
= "Biosystems",
volume
= "47",
number
= "1--2",
pages
= "1--7",
year = "1998",
url = "",
keywords
= "metabolism, knowledge
representation, graphical",
abstract
= "Problems involved in
representation of metabolism are dealt with. The specific characteristics of
the various ways (verbal, graphical and by electronic means), their advantages
and limitations are discussed. New developments in research pose challenges for
adequate and clear demonstration of results. Comments on nomenclature and on
style are included.",
crossref
= "PMID:9715748",
}
@InProceedings{Matsunoetal00,
author
= "H. Matsuno and A. Doi and
M. Nagasaki and S. Miyano",
title
= "Hybrid Petri net
representation of gene regulatory network",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "5",
pages
= "341--352",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/matsuno.pdf",
keywords
= "Petri net, hybrid,
quantitative, simulation, regulatory, implementation, stochastic, discrete,
continuous, hierarchical, modular",
abstract
= "It is important to provide a
representation method of gene regulatory networks which realizes the intuitions
of biologists while keeping the universality in its computational ability. In
this paper, we propose a method to exploit hybrid Petri net (HPN) for
representing gene regulatory networks. The HPN is an extension of Petri nets
which have been used to represent many kinds of systems including stochastic
ones in the field of computer sciences and engineerings. Since the HPN has
continuous and discrete elements, it can easily handle biological factors such
as protein and mRNA concentrations. We demonstrate that, by using HPNs, it is
possible to translate biological facts into HPNs in a natural manner. It should
be also emphasized that a hierarchical approach is taken for our construction
of the genetic switch mechanism of lambda phage which is realized by using
HPNs. This hierarchical approach with HPNs makes easier the arrangement of the
components in the gene regulatory network based on the biological facts and
provides us a prospective view of the network. We also show some computational
results of the protein dynamics of the lambda phage mechanism that is simulated
and observed by implementing the HPN on a currently available tool.",
crossref
= "PMID:10902182",
}
@InProceedings{Makietal01,
author
= "Y. Maki and D. Tominaga
and M. Okamoto and S. Watanabe and Y. Eguchi",
title
= "Development of a System
for the Inference of Large Scale Genetic Networks",
booktitle
= "Pacific Symposium on Biocomputing",
volume
= "6",
pages
= "446--458",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/maki.pdf",
keywords
= "reconstruction, Boolean
network, S-system, AIGNET, implementation, kinetic, mutation, regulatory",
abstract
= "We propose a system named
AIGNET (Algorithms for Inference of Genetic Networks), and introduce two
top-down approaches for the inference of interrelated mechanism among genes in
genetic network that is based on the steady state and temporal analyses of gene
expression patterns against some kinds of gene perturbations such as disruption
or overexpression. The former analysis is performed by a static Boolean network
model based on multi-level digraph, and the latter one is by S-system model. By
integrating these two analyses, we show our strategy is flexible and rich in
structure to treat gene expression patterns; we applied our strategy to the
inference of a genetic network that is composed of 30 genes as a case study.
Given the gene expression time-course data set under the conditions of
wild-type and the deletion of one gene, our system enabled us to reconstruct
the same network architecture as original one.",
crossref
= "",
}
@InProceedings{Moriyamaetal99,
author
= "T. Moriyama and A.
Shinohara and M. Takeda and O. Maruyama and T. Goto and S. Miyano and S.
Kuhara",
title
= "A System to Find Genetic
Networks Using Weighted Network Model",
booktitle
= "Genome Informatics",
volume = "10",
pages
= "186--195",
year = "1999",
editor
= "K. Asai and S. Miyano and
T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.jsbi.org/journal/GIW99/GIW99F19.pdf",
keywords
= "graph, reconstruction,
regulatory, visualization, analysis, mutation",
abstract
= "We are developing a system
which finds a genetic network from data obtained by multiple gene disruptions
and overexpressions. We deal with a genetic network as a weighted graph, where
each weight represents the strength of activation from a gene to another gene.
In this paper, we explain the overview of our system, and our strategy to
visualize the weighted network. We also study the computational complexity
related to the visualization.",
crossref
= "PMID:11072355",
}
@InProceedings{MericandWise99,
author
= "P. A. Meric and M. J.
Wise",
title
= "Quantitative, scalable
discrete-event simulation of metabolic pathways",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "7",
pages
= "187--194",
year = "1998",
editor = "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "http://www.cs.usyd.edu.au/~pmeric/Research/Bioinformatics/DMSS/ISMB99_A4.ps",
keywords
= "simulation, graph, discrete,
quantitative, implementation, DMSS, metabolism",
abstract
= "DMSS (Discrete Metabolic
Simulation System) is a framework for modelling and simulating metabolic
pathways. Quantitative simulation of metabolic pathways is achieved using
discrete-event techniques. The approach differs from most quantitative
simulators of metabolism which employ either time-differentiated functions or
mathematical modelling techniques. Instead, models are constructed from biochemical
data and biological knowledge, with accessibility and relevance to biologists
serving as key features of the system.",
crossref
= "PMID:10786301",
}
@InProceedings{Marnellosetal00,
author
= "G. Marnellos and G. A.
Deblandre and E. Mjolsness and C. Kintner",
title
= "Delta-Notch lateral
inhibitory patterning in the emergence of ciliated cells in Xenopus:
experimental observations and a gene network model",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "5",
pages
= "329--340",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/marnellos.pdf",
keywords
= "spatial, regulatory, neural
network, simulation, mutation",
abstract
= "In diverse vertebrate and
invertebrate systems, lateral inhibition through the Delta-Notch signaling
pathway can lead to cells in initially uniform epithelial tissues
differentiating in "salt-and-pepper", regular spacing patterns. In
this paper we examine lateral inhibition during the emergence of ciliated cells
in Xenopus embryonic skin, using experimental manipulations of the Delta-Notch
pathway and a connectionist gene-network model of the process. The results of
our model are in agreement with previous models of regular patterning through
lateral inhibition and reproduce the observations of our experimental assays.
Moreover, the model provides an account for the variability of embryonic
responses to the experimental assays, points to a component of lateral
inhibition that may be the chief source of this variability, and suggests ways
to control it. Our model could thus serve as a tool to generate predictions
about this and other regular patterning systems governed by lateral
inhibition.",
crossref
= "PMID:10902181",
}
@Article{Mjolsnessetal91,
author
= "E. Mjolsness and D. H.
Sharp and J. Reinitz",
title
= "A connectionist model of
development",
journal
= "Journal of Theoretical
Biology",
volume
= "152",
number
= "4",
pages
= "429--453",
year = "1991",
url = "",
keywords
= "spatial, regulatory, neural
network, grammar, mutation, simulation, kinetic",
abstract
= "We present a phenomenological
modeling framework for development. Our purpose is to provide a systematic
method for discovering and expressing correlations in experimental data on gene
expression and other developmental processes. The modeling framework is based
on a connectionist or "neural net" dynamics for biochemical
regulators, coupled to "grammatical rules" which describe certain
features of the birth, growth, and death of cells, synapses and other
biological entities. We outline how spatial geometry can be included, although
this part of the model is not complete. As an example of the application of our
results to a specific biological system, we show in detail how to derive a
rigorously testable model of the network of segmentation genes operating in the
blastoderm of Drosophila. To further illustrate our methods, we sketch how they
could be applied to two other important developmental processes: cell cycle
control and cell-cell induction. We also present a simple biochemical model
leading to our assumed connectionist dynamics which shows that the dynamics
used is at least compatible with known chemical mechanisms.",
crossref
= "PMID:1758194",
}
@InProceedings{MarnellosandMjolnessl98,
author
= "G. Marnellos and E.
Mjolsness",
title
= "A gene network approach
to modeling early neurogenesis in Drosophila",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "30--41",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/marnellos.pdf",
keywords
= "spatial, regulatory, neural
network, simulation, mutation",
abstract
= "We have produced a model of
genetic regulation to simulate how neuroblasts and sensory organ precursor
(SOP) cells differentiate from proneural clusters of equivalent cells.
Parameters of the model (mainly gene interaction strengths) are optimized in
order to fit schematic patterns of expression, drawn from the literature, of
genes that are involved in this process of cell fate specification. The model
provides suggestions about the role of lateral signalling in neurogenesis and
yields specific and testable predictions about the timing and position of
appearance of neuroblasts and SOPs within proneural clusters, and about the dynamics
of gene expression in individual cells. Experimental testing of these
predictions and fits to more accurate quantitative data will help determine
which set of model parameters can best describe early neurogenesis.",
crossref
= "PMID:9697169",
}
@InProceedings{Mittenthal97,
author
= "J. E. Mittenthal",
title
= "An algorithm to assemble
pathways from processes",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "2",
pages
= "292--303",
year = "1997",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www-smi.stanford.edu/people/altman/psb97/mittenthal.pdf",
keywords
= "signaling, metabolism,
regulatory, qualitative, combinatorial, pathway discovery,
reconstruction",
abstract
= "To understand or to modify a
biological pathway, the first step is to determine the patterns of coupling
among its processes that are compatible with its input-output relation.
Algorithms for this purpose have been devised for metabolic pathways, in which
the reactions typically leave the enzymes unmodified. As shown here, one of
these algorithms can also assemble molecular networks in which reactions modify
proteins, if the proteins are included among the inputs to the reactions. Thus
one procedure suffices to assemble pathways for metabolism, cytoplasmic signal
transduction, and gene regulation.",
crossref
= "PMID: 9390300",
}
@Article{MendozaandAlvarezBuylla98,
author
= "L. Mendoza and E. R.
Alvarez-Buylla",
title
= "Dynamics of the genetic
regulatory network for Arabidopsis thaliana flower morphogenesis",
journal
= "Journal of Theoretical
Biology",
volume
= "193",
number
= "2",
pages
= "307--319",
year = "1998",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1998.0701/pdf",
keywords
= "Boolean network, logic,
qualitative, constraints, simulation, mutation, regulatory, feedback,
analysis",
abstract
= "We present a network model
and its dynamic analysis for the regulatory relationships among 11 genes that
participate in Arabidopsis thaliana flower morphogenesis. The topology of the
network and the relative strengths of interactions among these genes were based
from published genetic and molecular data, mainly relying on mRNA expression
patterns under wild type and mutant backgrounds. The network model is made of
binary elements and we used a particular dynamic implementation for the network
that we call semi-synchronic. Using this method the network reaches six
attractors; four of them correspond to observed patterns of gene expression
found in the floral organs of Arabidopsis (sepals, petals, stamens and carpels)
as predicted by the ABC model of flower morphogenesis. The fifth state
corresponds to cells that are not competent to flowering, and the sixth
attractor predicted by the model is never found in wild-type plants, but it
could be induced experimentally. We discuss the biological implications and the
potential use of this network modeling approach to integrate functional data of
regulatory genes of plant development.",
crossref
= "PMID:9714934",
}
@Article{Mendozaetal99,
author
= "L. Mendoza and D. Thieffry
and E. R. Alvarez-Buylla",
title
= "Genetic control of flower
morphogenesis in Arabidopsis thaliana: a logical analysis",
journal
= "Bioinformatics",
volume
= "15",
number
= "7--8",
pages
= "593--606",
year = "1999",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/15/7/593.pdf",
keywords = "Boolean network, logic, qualitative,
logical constraints, simulation, mutation, regulatory, feedback,
analysis",
abstract
= "MOTIVATION: A large number
of molecular mechanisms at the basis of gene regulation have been described
during the last few decades. It is now becoming possible to address questions
dealing with both the structure and the dynamics of genetic regulatory
networks, at least in the case of some of the best-characterized organisms.
Most recent attempts to address these questions deal with microbial or animal
model systems. In contrast, we analyze here a gene network involved in the
control of the morphogenesis of flowers in a model plant, Arabidopsis thaliana.
RESULTS: The genetic control of flower morphogenesis in Arabidopsis involves a
large number of genes, of which 10 are considered here. The network topology
has been derived from published genetic and molecular data, mainly relying on
mRNA expression patterns under wild-type and mutant backgrounds. Using a
'generalized logical formalism', we provide a qualitative model and derive the
parameter constraints accounting for the different patterns of gene expression
found in the four floral organs of Arabidopsis (sepals, petals, stamens and
carpels), plus a 'non-floral' state. This model also allows the simulation or
the prediction of various mutant phenotypes. On the basis of our model
analysis, we predict the existence of a sixth stable pattern of gene
expression, yet to be characterized experimentally. Moreover, our dynamical analysis
leads to the prediction of at least one more regulator of the gene LFY, likely
to be involved in the transition from the non-flowering state to the flowering
pathways. Finally, this work, together with other theoretical and experimental
considerations, leads us to propose some general conclusions about the
structure of gene networks controlling development.",
crossref
= "PMID:10487867",
}
@Article{McAdamsandShapiro95,
author
= "H. H. McAdams and L.
Shapiro",
title
= "Circuit simulation of
genetic networks",
journal
= "Science",
volume
= "269",
number
= "5224",
pages
= "650--656",
year = "1995",
url = "",
keywords
= "circuit, simulation,
quantitative, regulatory, biochemical, kinetic, hybrid",
abstract
= "Genetic networks with tens
to hundreds of genes are difficult to analyze with currently available
techniques. Because of the many parallels in the function of these biochemically
based genetic circuits and electrical circuits, a hybrid modeling approach is
proposed that integrates conventional biochemical kinetic modeling within the
framework of a circuit simulation. The circuit diagram of the bacteriophage
lambda lysislysogeny decision circuit represents connectivity in signal paths
of the biochemical components. A key feature of the lambda genetic circuit is
that operons function as active integrated logic components and introduce
signal time delays essential for the in vivo behavior of phage lambda.",
crossref
= "PMID:7624793",
}
@Article{McAdamsandArkin97,
author
= "H. H. McAdams and A.
Arkin",
title
= "Stochastic mechanisms in
gene expression",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "94",
number
= "3",
pages
= "814--819",
year = "1997",
url = "http://www.pnas.org/cgi/reprint/94/3/814.pdf",
keywords
= "stochastic, simulation,
kinetic, biochemical, regulatory",
abstract
= "In cellular regulatory
networks, genetic activity is controlled by molecular signals that determine
when and how often a given gene is transcribed. In genetically controlled
pathways, the protein product encoded by one gene often regulates expression of
other genes. The time delay, after activation of the first promoter, to reach
an effective level to control the next promoter depends on the rate of protein
accumulation. We have analyzed the chemical reactions controlling transcript
initiation and translation termination in a single such "genetically
coupled" link as a precursor to modeling networks constructed from many
such links. Simulation of the processes of gene expression shows that proteins
are produced from an activated promoter in short bursts of variable numbers of
proteins that occur at random time intervals. As a result, there can be large
differences in the time between successive events in regulatory cascades across
a cell population. In addition, the random pattern of expression of competitive
effectors can produce probabilistic outcomes in switching mechanisms that
select between alternative regulatory paths. The result can be a partitioning
of the cell population into different phenotypes as the cells follow different
paths. There are numerous unexplained examples of phenotypic variations in
isogenic populations of both prokaryotic and eukaryotic cells that may be the
result of these stochastic gene expression mechanisms.",
crossref = "PMID:9023339",
}
@InProceedings{MccaskillandNiemann00,
author
= "J. McCaskill and U.
Niemann",
editor
= "",
booktitle
= "Proceedings of the sixth
international meeting on DNA based computers",
title
= "Graph Replacement
Chemistry for DNA Processing",
publisher
= "",
address
= "",
pages
= "89--99",
year = "2000",
url = "",
keywords
= "graph, biochemistry,
calculus, executable, grammar, nucleic acids, implementation,
qualitative",
abstract
= "The processing of nucleic
acids is abstracted using operators on directed and labeled graphs. This
provides a computational framework for predicting complex libraries of DNA/RNA
arising from sequences of reactions involving hybridization intermediates with
significant combinatorial complexity. It also provides a detailed functional
classification scheme for the reactions and side-reactions of DNA processing
enzymes. It is complementary to the conventional string-based DNA computing
grammars such as splicing systems, in that the graph-based structure of
enzyme-nucleic acid complexes is the fundamental object of combinatorial
manipulation and in that the allowed reactions are the allowed reactions are
specified by local graph replacement operators (i.e. catalysts for structural
transitions) associated with enzymes. The focus of the work is to present the
calculus for the compact specification and evaluation of the combined action of
multiple DNA-processing reactions. Each enzyme and its side reactions may be
classified by a small set of small graph replacement operators. Complex
replication and computation schemes may be computed with the formalism.",
}
@InProceedings{MccaskillandNiemann96,
author
= "J. McCaskill and U.
Niemann",
editor
= "",
booktitle
= "Computer Science and Biology:
German Conference on Bioinformatics (GCB'96)",
title = "Molecular Graph Reaction Networks",
series
= "Lecture Notes in Computer
Science",
number
= "1278",
publisher
= "Springer-Verlag",
address
= "",
pages
= "",
year = "1996",
url = "",
keywords
= "graph, biochemistry,
calculus, graph reaction networks",
abstract
= "",
}
@InProceedings{NgandWong99,
author
= "S. K. Ng and M.
Wong",
title
= "Toward Routine Automatic Pathway
Discovery from On-line Scientific Text Abstracts",
booktitle
= "Genome Informatics
1999",
volume
= "10",
pages
= "104--112",
year = "1999",
editor
= "K. Asai and S. Miyano and
T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.jsbi.org/journal/GIW99/GIW99F11.pdf",
keywords
= "visualization,
implementation, metabolism, BioJAKE, abstraction, type hierarchy, database,
pathway discovery, BioNLP, NLP, literature",
abstract
= "We are entering a new era of
research where the latest scientific discoveries are often first reported
online and are readily accessible by scientists worldwide. This rapid
electronic dissemination of research breakthroughs has greatly accelerated the
current pace in genomics and proteomics research. The race to the discovery of
a gene or a drug has now become increasingly dependent on how quickly a
scientist can scan through voluminous amount of information available online to
construct the relevant picture (such as protein-protein interaction pathways)
as it takes shape amongst the rapidly expanding pool of globally accessible
biological data (e.g. GENBANK) and scientific literature (e.g. MEDLINE). We
describe a prototype system for automatic pathway discovery from on-line text
abstracts, combining technologies that (1) retrieve research abstracts from
online sources, (2) extract relevant information from the free texts, and (3)
present the extracted information graphically and intuitively. Our work
demonstrates that this framework allows us to routinely scan online scientific
literature for automatic discovery of knowledge, giving modern scientists the
necessary competitive edge in managing the information explosion in this
electronic age.",
crossref
= "PMID:11072347",
}
@InProceedings{Nodaetal98,
author
= "K. Noda and A. Shinohara
and M. Takeda and S. Matsumoto and S. Miyano and S. Kuhara",
title
= "Finding Genetic Network
from Experiments by Weighted Network Model",
booktitle
= "Genome Informatics",
volume
= "9",
pages
= "141--150",
year = "1998",
editor
= "K. Asai and S. Miyano and T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.jsbi.org/journal/GIW98/GIW98F15.pdf",
keywords
= "graph, reconstruction, regulatory, visualization,
analysis, mutation",
abstract
= "We study the problem of
finding a genetic network from data obtained by multiple gene disruptions and
overexpressions. We define a genetic network as a weighted graph, and analyze
the computational complexity of the problem. We show that if there exists a
weighted network which is consistent with given data, we can find it in
polynomial time. Moreover, we also consider the optimization problem, where we
try to find an optimally consistent weighted network with given data. We show
that the problem is NP-hard. On the other hand, we give a polynomial-time
approximation algorithm to solve it with approximation ratio 2. We report some
simulation results on experiments.",
crossref
= "PMID:11072330",
}
@Article{NiandSavageau96,
author
= "T.C. Ni and M. A.
Savageau",
title
= "Model assessment and
refinement using strategies from biochemical systems theory: application to
metabolism in human red blood cells.",
journal
= "Journal of Theoretical
Biology",
volume
= "179",
number
= "4",
pages
= "329--368",
year = "1996",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1996.0072/pdf",
keywords
= "kinetic, power-law
formalism, mathematically controlled comparison, qualitative, analysis, comparative,
metabolism, robustness",
abstract
= "Models of biochemical
systems are typically formulated with kinetic data obtained from isolated
enzymes studied in vitro, and one has always to question whether or not all the
relevant metabolites, processes and regulatory interactions have been
identified and whether the parameter values obtained in vitro reflect the
actual intracellular environment. In this paper we extend and further test
strategies for model assessment and refinement that take advantage of the
power-law formalism, which provides the systematic structure underlying
biochemical systems theory. Our purpose is three fold. First, we introduce an
algorithm for systematically scanning a model for putative errors, which, if
corrected, would reconcile its behavior with the experimental system. Second,
we further test the working hypothesis that systems in nature are selected to
be robust and, hence, that the profile of parameter sensitivities can be used
to identify poorly defined regions of a model. Third, we illustrate the use of
these strategies within the context of a relatively large and realistic
biochemical system--the metabolic pathways of the human red blood cell. Our
results show that the reference model we have used is neither locally stable
nor robust. The algorithm identifies a number of putative regulatory
interactions that, when added to the model, are capable of stabilizing the
nominal steady state. We include one of these, the feedback inhibition of
hexokinase by fructose-6-phosphate, in a first refinement of the model because
there is experimental support for it in the literature. Careful re-examination
of the most sensitive section in this model, the pathways of nucleotide
metabolism, reveals two mechanisms that were omitted from the reference model:
membrane transport of adenosine and inosine, and regulation of phosphoribosyl
pyrophosphate synthetase by adenosine diphosphate, 2,3 diphosphoglycerate and
5-phosphoribosyl-1-pyrophosphate. It was also found that the concentration of
inorganic phosphate had been inappropriately assumed to be a constant.
Modifications to correct these deficiencies produced a second refinement of the
model whose parameter sensitivities are reduced on average by 10-fold. Although
these refinements are modest and there is substantial room for further
improvement, this application identified several biochemically relevant
features of the model that had been overlooked. It also points to nucleotide
metabolism as the area most in need of further experimental study.",
crossref
= "PMID:8763353",
}
@InProceedings{Nakaoetal98,
author
= "M. Nakao and H. Bono and
S. Kawashima and T. Kamiya and K. Sato and S. Goto and M. Kanehisa",
title
= "Genome-scale Gene
Expression Analysis and Pathway Reconstruction in KEGG",
booktitle
= "Genome Informatics",
volume
= "10",
pages
= "94-103",
year = "1999",
editor
= "K. Asai and S. Miyano and
T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.jsbi.org/journal/GIW99/GIW99F10.pdf",
keywords
= "KEGG, graphical, database,
signaling, metabolism, regulatory, reconstruction, pathway discovery",
abstract
= "The massively parallel
hybridization technologies by DNA chips and microarrays make it possible to
monitor expression patterns of the whole set of genes in a genome under various
conditions. The vast amount of data generated by such technologies necessitates
the development of a new database management system that integrates expression
data with other molecular biology databases and various analysis tools. We
report here an extension of our KEGG (Kyoto Encyclopedia of Genes and Genomes)
and DBGET/LinkDB systems for analyzing gene expression data in conjunction with
pathway information and genomic information. It is now possible to make use of
expression data for the reconstruction of pathways from the complete genome
sequences.",
crossref
= "PMID:11072346",
}
@InProceedings{Nagasakietal99,
author
= "M. Nagasaki and S. Onami
and S. Miyano and H. Kitano",
title
= "Bio-calculus: Its Concept
and Molecular Interaction",
booktitle
= "Genome Informatics",
volume
= "10",
pages
= "16--22",
year = "1999",
editor
= "K. Asai and S. Miyano and
T. Takagi",
publisher
= "Universal Academy
Press",
address
= "Tokyo",
url = "http://www.genome.ad.jp/manuscripts/GIW99/Oral/GIW99F14.pdf",
keywords
= "logic, calculus,
biochemistry, executable, simulation, quantitative, implementation,
Bio-Calculus",
abstract
= "The way for expressing
biological systems is a key element of usability. Expressions used in the
biological society and those in the computer science society have their own
merits. But they are too different for one society to utilize the expressions
of the other society. In this paper, we design the bio-calculus that attempts
to bridge this gap. We provide syntax which is similar to conventional
expressions in biology and at the same time specifies information needed for
simulation analysis. The information and mathematical background of
bio-calculus is what is desired for the field of computer science. We show the
practicality of bio-calculus by describing and simulating some molecular
interactions with bio-calculus.",
crossref
= "PMID:11072350",
}
@Article{Onoetal01,
author
= "T. Ono and H. Hishigaki
and A. Tanigami and T. Takagi",
title = "Automated extraction of information on protein-protein interactions from the biological literature",
journal
= "Bioinformatics",
volume
= "17",
number
= "2",
pages
= "155--161",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/2/155.pdf",
keywords
= "implementation,
protein-protein, reconstruction, literature, information extractio, NLP,
qualitative",
abstract
= "MOTIVATION: To understand
biological process, we must clarify how proteins interact with each other.
However, since information about protein-protein interactions still exists
primarily in the scientific literature, it is not accessible in a
computer-readable format. Efficient processing of large amounts of interactions
therefore needs an intelligent information extraction method. Our aim is to
develop an efficient method for extracting information on protein-protein
interaction from scientific literature. RESULTS: We present a method for
extracting information on protein-protein interactions from the scientific
literature. This method, which employs only a protein name dictionary, surface
clues on word patterns and simple part-of-speech rules, achieved high recall
and precision rates for yeast (recall = 86.8% and precision = 94.3%) and
Escherichia coli (recall = 82.5% and precision = 93.5%). The result of
extraction suggests that our method should be applicable to any species for
which a protein name dictionary is constructed. AVAILABILITY: The program is
available on request from the authors.",
crossref
= "PMID:11238071",
}
@Article{Ogataetal00,
author
= "H. Ogata and W. Fujibuchi
and S. Goto and M. Kanehisa",
title = "A heuristic graph comparison algorithm and its application to detect functionally related enzyme clusters ",
journal
= "Nucleic Acids
Research",
volume
= "28",
number
= "20",
pages
= "4021--4028",
year = "2000",
url = "http://nar.oupjournals.org/cgi/reprint/28/20/4021.pdf",
keywords
= "graph, KEGG, comparative,
whole genome, metabolism, analysis, qualitative",
abstract
= "The availability of
computerized knowledge on biochemical pathways in the KEGG database opens new
opportunities for developing computational methods to characterize and
understand higher level functions of complete genomes. Our approach is based on
the concept of graphs; for example, the genome is a graph with genes as nodes
and the pathway is another graph with gene products as nodes. We have developed
a simple method for graph comparison to identify local similarities, termed
correlated clusters, between two graphs, which allows gaps and mismatches of
nodes and edges and is especially suitable for detecting biological features.
The method was applied to a comparison of the complete genomes of 10
microorganisms and the KEGG metabolic pathways, which revealed, not
surprisingly, a tendency for formation of correlated clusters called FRECs
(functionally related enzyme clusters). However, this tendency varied
considerably depending on the organism. The relative number of enzymes in FRECs
was close to 50% for Bacillus subtilis and Escherichia coli, but was <10%
for SYNECHOCYSTIS: and Saccharomyces cerevisiae. The FRECs collection is
reorganized into a collection of ortholog group tables in KEGG, which
represents conserved pathway motifs with the information about gene clusters in
all the completely sequenced genomes.",
crossref
= "PMID:11024183",
}
@Article{Ogataetal00,
author
= "H. Ogata and S. Goto and
K. Sato and W. Fujibuchi and H. Bono and M. Kanehisa",
title
= "KEGG: Kyoto Encyclopedia
of Genes and Genomes",
journal
= "Nucleic Acids
Research",
year = "2000",
volume
= "27",
number
= "1",
pages
= "29--34",
url = "http://nar.oupjournals.org/cgi/reprint/27/1/29.pdf",
keywords
= "KEGG, database, regulatory,
graphical, signaling, metabolism, visualization, implementation",
abstract
= "Kyoto Encyclopedia of Genes
and Genomes (KEGG) is a knowledge base for systematic analysis of gene
functions in terms of the networks of genes and molecules. The major component
of KEGG is the PATHWAY database that consists of graphical diagrams of
biochemical pathways including most of the known metabolic pathways and some of
the known regulatory pathways. The pathway information is also represented by
the ortholog group tables summarizing orthologous and paralogous gene groups
among different organisms. KEGG maintains the GENES database for the gene
catalogs of all organisms with complete genomes and selected organisms with
partial genomes, which are continuously re-annotated, as well as the LIGAND
database for chemical compounds and enzymes. Each gene catalog is associated
with the graphical genome map for chromosomal locations that is represented by
Java applet. In addition to the data collection efforts, KEGG develops and
provides various computational tools, such as for reconstructing biochemical
pathways from the complete genome sequence and for predicting gene regulatory
networks from the gene expression profiles. The KEGG databases are daily
updated and made freely available (http://www.genome.ad.jp/kegg/).",
crossref
= "PMID:9847135",
}
@Article{Ogataetal00,
author
= "H. Ogata and S. Goto and
W. Fujibuchi and M. Kanehisa",
title
= "Computation with the KEGG
pathway database",
journal
= "Biosystems",
year = "1998",
volume
= "47",
number
= "1--2",
pages
= "119--128",
url = "",
keywords
= "inference, reconstruction,
graphical, KEGG, database, pathway discovery",
abstract
= "We introduce and discuss a
new computational approach towards prediction and inference of biological
functions from genomic sequences by making use of the pathway data in KEGG. Due
to its piecewise nature, the current approach of predicting each gene function
based on sequence similarity searches often fails to reconstruct cellular
functions with all necessary components. The pathway diagram in KEGG, which may
be considered a wiring diagram of molecules in biological systems, can be
utilised as a reference for functional reconstruction. KEGG also contains
binary relations that represent molecular interactions and relations and that
can be utilised for computing and comparing pathways.",
crossref
= "PMID:9521924",
}
@Article{Peeretal01,
author
= "D. Pe'er and A. Regev and
G. Elidan and N. Friedman",
title = "Inferring subnetworks from perturbed expression profiles ",
journal
= "Bioinformatics",
volume
= "17",
number
= "",
pages
= "S215--S224",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/suppl_1/S215.pdf",
keywords = "regulatory, reconstruction, Bayesian network, inference, implementation, Pathway Explorer, visualization, graph, mutation",
abstract
= "Genome-wide expression
profiles of genetic mutants provide a wide variety of measurements of cellular
responses to perturbations. Typical analysis of such data identifies genes
affected by perturbation and uses clustering to group genes of similar
function. In this paper we discover a finer structure of interactions between
genes, such as causality, mediation, activation, and inhibition by using a
Bayesian network framework. We extend this framework to correctly handle
perturbations, and to identify significant subnetworks of interacting genes. We
apply this method to expression data of S. cerevisiae mutants and uncover a
variety of structured metabolic, signaling and regulatory pathways.",
crossref
= "PMID:11473012",
}
@Article{Pirsonetal00,
author
= "I. Pirson and N.
Fortemaison and C. Jacobs and S. Dremier and J. E. Dumont and C.
Maenhaut",
title = "The visual display of regulatory information and networks
",
journal
= "Trends in Cell
Biology",
volume
= "10",
number
= "10",
pages
= "404--408",
year = "2000",
keywords
= "graphical, visualization,
metabolism, regularoty, signaling, protein-protein, knowledge representation,
qualitative, domain",
abstract
= "Cell regulation and signal
transduction are becoming increasingly complex, with reports of new
cross-signalling, feedback, and feedforward regulations between pathways and
between the multiple isozymes discovered at each step of these pathways.
However, this information, which requires pages of text for its description,
can be summarized in very simple schemes, although there is no consensus on the
drawing of such schemes. This article presents a simple set of rules that
allows a lot of information to be inserted in easily understandable
displays.",
crossref
= "PMID:10998591",
}
@Unpublished{pathdb00,
author = "",
title = "PathDB: A Metabolic Pathway
Database",
year = "2000",
url = "http://www.ncgr.org/research/pathdb/",
keywords
= "metabolism, database,
implementation, PathDB, visualization, pathway discovery, kinetic, simualtion,
Gepasi, analysis, flux balancing, steady state, flux route ",
abstract
= "NCGR is developing a general
metabolic pathway database that will represent current knowledge of metabolism.
PathDB is unique in that it will not be restricted to the pathways that
curators have defined but it will be able to discover any paths between
metabolites",
crossref
=
"http://www.ncgr.org/software/pathdb/",
}
@Article{Pellegrinietal99,
author
= "M. Pellegrini and E. M.
Marcotte and M. J. Thompson and D. Eisenberg and T. O. Yeates",
title = "Assigning protein functions by comparative genome analysis: protein phylogenetic profiles ",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "96",
number
= "8",
pages
= "4285--4288",
year = "1999",
url = "http://www.pubmedcentral.nih.gov/picrender.cgi?artid=5436&pictype=5",
keywords
= "comparative, reconstruction,
phylogenetic profile, signaling, metabolism, protein-protein, interaction map,
graph, analysis, whole genome, qualitative, pathway discovery",
abstract = "Determining protein functions from genomic sequences is a central goal of bioinformatics. We present a method based on the assumption that proteins that function together in a pathway or structural complex are likely to evolve in a correlated fashion. During evolution, all such functionally linked proteins tend to be either preserved or eliminated in a new species. We describe this property of correlated evolution by characterizing each protein by its phylogenetic profile, a string that encodes the presence or absence of a protein in every known genome. We show that proteins having matching or similar profiles strongly tend to be functionally linked. This method of phylogenetic profiling allows us to predict the function of uncharacterized proteins.",
crossref
= "PMID:10200254",
}
@Article{Pfeifferetal99,
author
= "T. Pfeiffer and I.
Sanchez-Valdenebro and J. C. Nuno and F. Montero and S. Schuster",
title = "METATOOL: for studying metabolic networks",
journal
= "Bioinformatics",
volume
= "15",
number
= "3",
pages
= "251--257",
year = "1999",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/15/3/251.pdf",
keywords
= "METATOOL, implementation,
flux route, reconstruction, kinetic, quantitative, analysis, metabolism,
algebraic, stoichiometry",
abstract
= "MOTIVATION: To reconstruct
metabolic pathways from biochemical and/or genome sequence data, the
stoichiometric and thermodynamic feasibility of the pathways has to be tested.
This is achieved by characterizing the admissible region of flux distributions
in steady state. This region is spanned by what can be called a convex basis.
The concept of 'elementary flux modes' provides a mathematical tool to define
all metabolic routes that are feasible in a given metabolic network. In
addition, we define 'enzyme subsets' to be groups of enzymes that operate
together in fixed flux proportions in all steady states of the system. RESULTS:
Algorithms for computing the convex basis and elementary modes developed
earlier are briefly reviewed. A newly developed algorithm for detecting all
enzyme subsets in a given network is presented. All of these algorithms have
been implemented in a novel computer program named METATOOL, whose features are
outlined here. The algorithms are illustrated by an example taken from sugar
metabolism. AVAILABILITY: METATOOL is available from
ftp://bmsdarwin.brookes.ac. uk/pub/software/ibmpc/metatool. SUPPLEMENTARY
INFORMATION: http://www.
biologie.hu-berlin.de/biophysics/Theory/tpfeiffer/metatoo l.html",
crossref
= "PMID:10222413",
}
@InProceedings{Prouxetal00,
author
= "D. Proux and F. Rechenmann
and L. Julliard",
title
= "A pragmatic information
extraction strategy for gathering data on genetic",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume = "8",
pages
= "279--285",
year = "2000",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "ftp://ftp.sdsc.edu/pub/sdsc/biology/ISMB00/019.pdf",
keywords
= "literature, NLP, information
extraction, regulatory, conceptual graph",
abstract
= "We present in this paper a
pragmatic strategy to perform information extraction from biologic texts. Since
the emergence of the information extraction field, techniques have evolved,
become more robust and proved their efficiency on specific domains. We are
using a combination of existing linguistic and knowledge processing tools to
automatically extract information about gene interactions in the literature.
Our ultimate goal is to build a network of gene interactions. The methodologies
used and the current results are discussed in this paper.",
crossref
= "PMID:10977089",
}
@Article{Patonetal00,
author
= "N. W. Paton and S. A. Khan
and A. Hayes and F. Moussouni and A. Brass and K. Eilbeck and C. A. Goble and
S. J. Hubbard and S. G. Oliver",
title
= "Conceptual modelling of
genomic information",
journal
= "Bioinformatics",
year = "2000",
volume
= "16",
number
= "6",
pages
= "548--557",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/6/548.pdf",
keywords
= "UML, Unified Modeling
Language, ontology, object-oriented, implementation, TAMBIS,GIMS,
protein-protein",
abstract
= "Motivation: Genome
sequencing projects are making available complete records of the genetic
make-up of organisms. These core data sets are themselves complex, and present
challenges to those who seek to store, analyse and present the information.
However, in addition to the sequence data, high throughput experiments are
making available distinctive new data sets on protein interactions, the
phenotypic consequences of gene deletions, and on the transcriptome, proteome,
and metabolome. The effective description and management of such data is of
considerable importance to bioinformatics in the post-genomic era. The
provision of clear and intuitive models of complex information is surprisingly
challenging, and this paper presents conceptual models for a range of important
emerging information resources in bioinformatics. It is hoped that these can be
of benefit to bioinformaticians as they attempt to integrate genetic and
phenotypic data with that from genomic sequences, in order to both assign gene
functions and elucidate the different pathways of gene action and interaction.
Results: This paper presents a collection of conceptual (i.e.
implementation-independent) data models for genomic data. These conceptual
models are amenable to (more or less direct) implementation on different
computing platforms. Availability: Most of the information models presented
here have been implemented by the authors using an object database. The
implementation of a public interface to this database is in progress. We hope
to have a public release in the autumn of 2000, available from
http://img.cs.man.ac. uk/gims.",
crossref
= "PMID:10980152",
}
@Article{Priamietal01,
author
= "C. Priami and A. Regev and
E. Shapiro and W. Silverman",
title = "Application of a stochastic name-passing calculus to representation
and simulation of molecular processes",
journal
= "Information Processing
Letters",
volume
= "",
number
= "",
pages
= "",
note = “in press”
year = "2001",
url = "http://www.wisdom.weizmann.ac.il/~aviv/ipl.ps",
keywords
= "logic, pi-calculus,
signaling, stochastic, quantitative, implementation, simulation, BioPSI,
calculus, executable, mutation, formal verification",
abstract
= "We describe a novel
application of a stochastic name passing calculus for the study of biomolecular
systems. We specify the structure and dynamics of biochemical networks in a
variant of the stochastic pi-calculus, yielding a model which is mathematically
well-defined and biologically faithful. We adapt the operational semantics of
the calculus to account for both the time and probability of biochemical
reactions, and present a computer implementation of the calculus for
biochemical simulations.",
crossref
= "",
}
@InProceedings{RomeroandKarp01,
author
= "P. R. Romero and P.
Karp",
title
= "Nutrition-Related Analysis
of Pathway/Genome Databases",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "6",
pages
= "470--482",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/romero.pdf",
keywords
= "metabolism, database,
implementation, EcoCyc, reconstruction, pathway discovery, inference, whole
genome, frames",
abstract = "We present an algorithm that solves two related problems in the analysis of metabolic networks stored within a pathway/genome database. (1) The Forward Propagation Problem: given a set of nutrients that are inputs to the metabolic network, what compounds will be produced by the metabolic network? (2) The Backtracking Problem: given the results of a forward propagation, and given a set of essential compounds that are not produced as a result of the forward propagation, what precursors must be supplied to produce those essential compounds? A program based on this algorithm is applied to the EcoCyc database, which is a pathway/genome database for E. coli that consists of annotated genomes and the metabolic reactions and pathways associated with the known gene products. The inputs to the program are a description of the metabolic network of an organism (EcoCyc), a set of nutrients corresponding to a known minimal growth medium, and a list of essential compounds to be produced. The program "fires" the microorganism's metabolism contained in the database and predicts all synthesized and non-synthesized essential compounds, along with the missing precursors required to produce the latter. When applied to the EcoCyc database, the program identifies a number of missing precursors that indicate incomplete regions of the database. Thus the program results can be used to evaluate existing pathway databases like EcoCyc.",
crossref
= "",
}
@Article{Rainetal01,
author
= "J. C. Rain and L. Selig and H. De Reuse and V. Battaglia
and C. Reverdy and S. Simon and G. Lenzen and F. Petel and J. Wojcik and V. Schachter
and Y. Chemama and A. Labigne and P. Legrain",
title = "The
protein--protein interaction map of Helicobacter pylori ",
journal
= "Nature",
volume
= "409",
number
= "",
pages
= "211--215",
year = "2001",
keywords
= "protein-protein,
implementation, visualization, reconstruction, PIMRider, graphical, domain,
interactive, interaction map",
abstract
= "With the availability of complete DNA sequences for many
prokaryotic and eukaryotic genomes, and soon for the human genome itself, it is
important to develop reliable proteome-wide approaches for a better
understanding of protein function. As elementary constituents of cellular
protein complexes and pathways, protein–protein interactions are key
determinants of protein function. Here we have built a large-scale
protein–protein interaction map of the human gastric pathogen Helicobacter
pylori. We have used a high-throughput strategy of the yeast two-hybrid assay
to screen 261 H. pylori proteins against a highly complex library of
genome-encoded polypeptides. Over 1,200 interactions were identified between H.
pylori proteins, connecting 46.6% of the proteome. The determination of a
reliability score for every single protein–protein interaction and the
identification of the actual interacting domains permitted the assignment of
unannotated proteins to biological pathways.",
crossref
= "",
}
@Article{Robertsetal00,
author
= "C. J. Roberts and B.
Nelson and M. J. Marton and R. Stoughton and M. R. Meyer and H. A. Bennett and
Y. D. He and H. Dai and W. L. Walker and T. R. Hughes and M. Tyers and C. Boone
and S. H. Friend",
title = "Signaling and circuitry of multiple MAPK pathways
revealed by a matrix of global gene expression profiles ",
journal
= "Science",
volume
= "287",
number
= "5454",
pages
= "873--880",
year = "2000",
url = "http://www.sciencemag.org/cgi/reprint/287/5454/873.pdf",
keywords
= "signaling, reconstruction,
qualitative, analysis, mutation, pathway discovery",
abstract
= "Genome-wide transcript
profiling was used to monitor signal transduction during yeast pheromone
response. Genetic manipulations allowed analysis of changes in gene expression
underlying pheromone signaling, cell cycle control, and polarized
morphogenesis. A two-dimensional hierarchical clustered matrix, covering 383 of
the most highly regulated genes, was constructed from 46 diverse experimental
conditions. Diagnostic subsets of coexpressed genes reflected signaling
activity, cross talk, and overlap of multiple mitogen-activated protein kinase
(MAPK) pathways. Analysis of the profiles specified by two different
MAPKs-Fus3p and Kss1p-revealed functional overlap of the filamentous growth and
mating responses. Global transcript analysis reflects biological responses
associated with the activation and perturbation of signal transduction
pathways.",
crossref
= "PMID:10657304",
}
@InProceedings{Rindfleschetal99,
author
= "T. C. Rindflesch and L.
Hunter and A. R. Aronson",
title
= "Mining molecular binding
terminology from biomedical text",
booktitle
= "Proceedings of the AMIA
Symposium 1999",
volume
= "",
pages
= "127--131",
year = "1999",
editor
= "",
publisher
= "",
address
= "",
url = "http://www.amia.org/pubs/symposia/D005564.PDF",
keywords
= "knowledge representation,
visualization, UMLS, ontology, literature, NLP, protein-protein, binding,
biochemistry, information extraction",
abstract
= "Automatic access to
information regarding macromolecular binding relationships would provide a
valuable resource to the biomedical community. We report on a pilot project to
mine such information from the molecular biology literature. The program being
developed takes advantage of natural language processing techniques and is
supported by two repositories of biomolecular knowledge. A formative evaluation
has been conducted on a subset of MEDLINE abstracts.",
crossref
= "PMID:10566334",
}
@Article{Rzhetskyetal00,
author
= "A. Rzhetsky and T. Koike
and S. Kalachikov and S.M. Gomez and M. Krauthammer and S.H. Kaplan and P. Kra
and J.J. Russo and C. Friedman",
title
= "A Knowledge Model for
Analysis and Simulation of Regulatory Networks",
journal
= "Bioinformatics",
year = "2000",
volume
= "16",
number
= "12",
pages
= "1120--1128",
note = "",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/12/1120.pdf",
keywords
= "ontology, signaling,
regulatory, visualization, biochemistry, knowledge representation,
compartment",
abstract = "Motivation. In order to aid in hypothesis-driven experimental gene discovery, we are designing a computer application for the automatic retrieval of signal transduction data from electronic versions of scientific publications using natural language processing (NLP)techniques, as well as for visualizing and editing representations of regulatory systems. These systems describe both signal transduction and biochemical pathways within complex multicellular organisms, yeast, and bacteria. This computer application in turn requires the development of a domain-specific ontology, or knowledge model. Results: We introduce an ontological model for the representation of biological knowledge related to regulatory networks in vertebrates. We outline a taxonomy of the concepts, define their "whole-to-part" relationships, describe the properties of major concepts, and outline a set of the most important axioms. The ontology is partially realized in a computer system designed to aid researchers in biology and medicine in visualizing and editing a representation of a signal transduction system. Availability: The knowledge model can be reviewed at http://genome6.cpmc.columbia.edu/tkoike/ontology/",
crossref = "PMID:11159331",
}
@InProceedings{Regevetal01,
author
= "A. Regev and W. Silverman
and E. Shapiro",
title
= "Representation and
Simulation of Biochemical Processes Using the pi- Calculus Process
Algebra",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "6",
pages
= "459--470",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/regev.pdf",
keywords
= "logic, pi-calculus,
signaling, semi-quantitative, implementation, simulation, BioPSI, calculus,
executable, mutation, formal verification",
abstract
= "Despite the rapidly
accumulating body of knowledge about protein networks, there is currently no
convenient way of sharing and manipulation of such information. We suggest that
a formal computer language for describing the biomolecular processes underlying
protein networks is essential for rapid advancement in this field. We propose
to model biomolecular processes by using the pi-Calculus, a process algebra,
originally developed for describing computer processes. Our model for
biochemical processes is mathematically well-defined, while remaining
biologically faithful and transparent. It is amenable to computer simulation,
analysis and formal verification. We have developed a computer simulation system,
the PiFCP, for execution and analysis of pi-calculus programs. The system
allows us to trace, debug and monitor the behavior of biochemical networks
under various manipulations. We present a pi-calculus model for the RTK-MAPK
signal transduction pathway, formally represent detailed molecular and
biochemical information, and study it by various PiFCP simulations.",
crossref
= "",
}
@TechReport{Sauro01,
author = "H. M. Sauro",
title = "Jarnac -Scamp II: Reference
Guide",
institution = "",
year = "2000",
month = "",
note = "",
url = "http://members.tripod.co.uk/sauro/Downloads/JRef_A4.pdf",
keywords
= "implementation, simulation,
Jarnac, metabolism, kinetic",
abstract
= "Jarnac is an interactive and
interpreted language for modelling integrated cellular systems,such as
metabolic, gene regulation and signal transduction
circuits. This document is a summary
of the current state of Jarnac.Since Jarnac is still under development the specifications outlined here may change at a future
date. The purpose of Jarnac is to
help people model and study the internal networks and dynamics of living cells. It does this by enabling a user to describe the many
and varied chemical processes that go on in cells using a syntax familiar to the average biologist or
chemist.Thus Jarnac allows a researcher to describe cells in terms of metabolites,enzyme,signals and so on and avoids
the user having to write down differential equations or work out whether there are conservation relations or
not.The mathematical and technical side is all done in the background which enables a researcher to
concentrate on the scientific questions at hand. To
support the ability to model cellular systems, Jarnac provides a rich scripting
language to control,build and manipulate models.Jarnac
can manipulate a variety of data types,from simple integers,to floating point numbers,to vectors,matrices and so on. The
Jarnac scripting language supports the usual language constructs,such as looping,conditionals,user
functions and modules.Modules and user functions are a powerful feature that allow users to extend Jarnac
’s capability. Jarnac is also an interactive environment, thus a user issues commands or executes scripts at a
console window with the results being immediately returned
to the user for inspection.This rapid feedback of results,enables a user to
quickly learn how to use Jarnac and helps them get
closer to the biological problem.",
crossref
= "",
}
@Article{Sanchezetal99,
author = "C. Sanchez and C. Lachaize and F. Janody and B. Bellon and L. Roder and J. Euzenat and F. Rechenmann F, and B. Jacq", title = "Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an Internet database",
journal
= "Nucleic Acids
Research",
volume
= "27",
number
= "1",
pages
= "89--94",
year = "1999",
url = "http://nar.oupjournals.org/cgi/reprint/27/1/89.pdf",
keywords
= "protein-protein, regulatory,
molecular, database, implementation, FlyNets, visualization",
abstract
= "FlyNets
(http://gifts.univ-mrs.fr/FlyNets/FlyNets_home_page.++ +html) is a WWW database
describing molecular interactions (protein-DNA, protein-RNA and protein-protein)
in the fly Drosophila melanogaster. It is composed of two parts, as follows.
(i) FlyNets-base is a specialized database which focuses on molecular
interactions involved in Drosophila development. The information content of
FlyNets-base is distributed among several specific lines arranged according to
a GenBank-like format and grouped into five thematic zones to improve human
readability. The FlyNets database achieves a high level of integration with
other databases such as FlyBase, EMBL, GenBank and SWISS-PROT through numerous
hyperlinks. (ii) FlyNets-list is a very simple and more general databank, the
long-term goal of which is to report on any published molecular interaction
occuring in the fly, giving direct web access to corresponding s in Medline and
in FlyBase. In the context of genome projects, databases describing molecular
interactions and genetic networks will provide a link at the functional level
between the genome, the proteome and the transcriptome worlds of different
organisms. Interaction databases therefore aim at describing the contents,
structure, function and behaviour of what we herein define as the interactome
world.",
crossref
= "PMID:9847149",
}
@Article{SantillanandMackey01,
author
= "M. Santillan and M. C. Mackey",
title = "Dynamic regulation of the tryptophan operon: A modeling study and comparison with experimental data.",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "98",
number
= "4",
pages
= "1364--1369",
year = "2001",
url = "http://www.pnas.org/cgi/reprint/98/4/1364.pdf",
keywords
= "kinetic, analysis,
regulatory, temporal, biochemistry, simulation, delay differential
equations",
abstract
= "A mathematical model for
regulation of the tryptophan operon is presented. This model takes into account
repression, feedback enzyme inhibition, and transcriptional attenuation.
Special attention is given to model parameter estimation based on experimental
data. The model's system of delay differential equations is numerically solved,
and the results are compared with experimental data on the temporal evolution
of enzyme activity in cultures of Escherichia coli after a nutritional shift
(minimal + tryptophan medium to minimal medium). Good agreement is obtained
between the numeric simulations and the experimental results for wild-type E.
coli, as well as for two different mutant strains.",
crossref
= "PMID:11171956",
}
@Article{Selkovetal98,
author
= "E. Selkov and Y. Grechkin
and N. Mikhailova and E. Selkov",
title = "MPW: the Metabolic Pathways Database",
journal
= "Nucleic Acids
Research",
volume
= "26",
number
= "1",
pages
= "43--45",
year = "1998",
url = "http://nar.oupjournals.org/cgi/reprint/26/1/43.pdf",
keywords
= "database, implementation,
MPW, EMP, WIT2, visualization, metabolism, reconstruction, PUMA, signaling,
regulatory, graphical, kinetic, stoichiometry,
whole genome, comparative, compartment, transport",
abstract
= "The Metabolic Pathwasy
Database (MPW) (www.biobase.com/emphome.html/homepage. html.pags/pathways.html)
a derivative of EMP (www.biobase.com/EMP) plays a fundamental role in the
technology of metabolic reconstructions from sequenced genomes under the PUMA
(www.mcs.anl.gov/home/compbio/PUMA/Production/
ReconstructedMetabolism/reconstruction.html), WIT
(www.mcs.anl.gov/home/compbio/WIT/wit.html ) and WIT2
(beauty.isdn.msc.anl.gov/WIT2.pub/CGI/user.cgi) systems. In October 1997, it
included some 2800 pathway diagrams covering primary and secondary metabolism,
membrane transport, signal transduction pathways, intracellular traffic,
translation and transcription. In the current public release of MPW (beauty.isdn.mcs.anl.gov/MPW),
the encoding is based on the logical structure of the pathways and is
represented by the objects commonly used in electronic circuit design. This
facilitates drawing and editing the diagrams and makes possible automation of the
basic simulation operations such as deriving stoichiometric matrices, rate
laws, and, ultimately, dynamic models of metabolic pathways. Individual pathway
diagrams, automatically derived from the original ASCII records, are stored as
SGML instances supplemented by relational indices. An auxiliary database of
compound names and structures, encoded in the SMILES format, is maintained to
unambiguously connect the pathways to the chemical structures of their
intermediates.",
crossref
= "PMID:9407141",
}
@Article{Selkovetal96,
author
= "E. Selkov and S. Basmanova
and T. Gaasterland and I. Goryanin and Y. Gretchkin and N. Maltsev and V.
Nenashev and R. Overbeek and E. Panyushkina and L. Pronevitch and E. Selkov E
and I. Yunus ",
title = "The metabolic pathway collection from EMP: the enzymes and metabolic pathways database.",
journal
= "Nucleic Acids
Research",
volume
= "24",
number
= "1",
pages
= "26--28",
year = "1996",
url = "http://nar.oupjournals.org/cgi/reprint/24/1/26.pdf",
keywords
= "database, implementation, EMP,
visualization, metabolism, reconstruction, graphical, kinetic, stoichiometry, whole genome, comparative,
PUMA",
abstract
= "The Enzymes and Metabolic
Pathways database (EMP) is an encoding of the contents of over 10 000 original
publications on the topics of enzymology and metabolism. This large body of
information has been transformed into a queryable database. An extraction of
over 1800 pictorial representations of metabolic pathways from this collection
is freely available on the World Wide Web. We believe that this collection will
play an important role in the interpretation of genetic sequence data, as well
as offering a meaningful framework for the integration of many other forms of
biological data.",
crossref
= "PMID:8594593",
}
@Unpublished{spad00,
author = "",
title = "SPAD signaling pathway
database",
year = "2000",
url = "http://www.grt.kyushu-u.ac.jp/spad/",
keywords
= "signaling, regulatory,
visualization, graphical, database ",
abstract
= "The Signaling PAthway
Database (SPAD) is an integrated database for genetic information and signal
transduction systems. There are multiple signal transduction pathways: cascade
of information from plasma membrane to nucleus in response to an extracellular
stimulus in living organisms. Extracellular signal molecule binds specific
intracellular receptor, and initiates the signaling pathway. Now, there is a
large amount of information about the signaling pathway which controls the gene
expression and cellular proliferation. We have developed an integrated database
SPAD to understrand the overview of signaling transduction. SPAD is divided to
four categories based on extracellular signal molecules (Growth factor,
Cytokine, and Hormone) and stress, that initiate the intracellular signaling
pathway. SPAD is compiled in order to descrive information on interaction
between protein and protein, protein and DNA as well as information on
sequences of DNA and proteins.",
crossref
= "",
}
@Unpublished{Selkov00,
author = "G. Selkov",
title = "Electronic arc",
year = "2000",
url = "http://home.xnet.com/~selkovjr/ElectricArc/",
keywords
= "visualization,
implementation, Electronic Arc, metabolism, graph",
abstract
= "With varying degrees of
convenience, ElectricArc can be
used to design everything from abstract graphs to electronic circuits, database
schema, computer networks and metabolic pathways. At the moment, I have only
included examples for metabolic pathways; examples for other areas of
application will soon follow. ElectricArc represents an attempt to borrow the
most generally useful ideas from
electronic CAD technology. It is based on two abstract graph objects, Node and
Arc. The code consists of the two tools named symbol and net, the former being
used to create the data and symbols for Nodes, while the latter serves the task
of laying out the networks of Nodes by connecting them with Arcs. Like a markup language that makes the
content of a man-written text understandable or processible to machines by inserting special tags in it, the data format used
by ElectricArc conveys the meaning of the man-made graphics by associating
individual primitives or groups of primitives with descriptive keywords and
data values.",
crossref
= "",
}
@Article{Schusteretal99,
author
= "S. Schuster and T.
Dandekar and D. A. Fell",
title = "Detection of elementary flux modes in biochemical
networks: a promising tool for pathway analysis and metabolic
engineering.",
journal
= "Trends in
Biotechnology",
volume
= "17",
number
= "2",
pages
= "53--60",
year = "1999",
keywords
= "metabolism, analysis,
kinetic, flux route, steady state, stoichiometry, quantitative, reconstruction,
engineering, topology",
abstract
= "Rational metabolic
engineering requires powerful theoretical methods such as pathway analysis, in
which the topology of metabolic networks is considered. All metabolic
capabilities in steady states are composed of elementary flux modes, which are
minimal sets of enzymes that can each generate valid steady states. The modes
of the fructose-2,6-bisphosphate cycle, the combined
tricarboxylic-acid-glyoxylate-shunt system and tryptophan synthesis are used
here for illustration. This approach can be used for many biotechnological
applications such as increasing the yield of a product, channelling a product
into desired pathways and in functional reconstruction from genomic
data.",
crossref
= "PMID:10087604",
}
@Article{Schusteretal00,
author
= "S. Schuster and D. A. Fell
and T. Dandekar",
title = "A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks",
journal
= "Nature Biotechnology",
volume
= "18",
number
= "3",
pages
= "326--332",
year = "2000",
keywords
= "metabolism, analysis,
kinetic, flux route, steady state, stoichiometry, quantitative, reconstruction,
engineering, topology",
abstract
= "A set of linear pathways
often does not capture the full range of behaviors of a metabolic network. The
concept of 'elementary flux modes' provides a mathematical tool to define and
comprehensively describe all metabolic routes that are both stoichiometrically
and thermodynamically feasible for a group of enzymes. We have used this
concept to analyze the interplay between the pentose phosphate pathway (PPP)
and glycolysis. The set of elementary modes for this system involves
conventional glycolysis, a futile cycle, all the modes of PPP function
described in biochemistry textbooks, and additional modes that are a priori
equally entitled to pathway status. Applications include maximizing product yield
in amino acid and antibiotic synthesis, reconstruction and consistency checks
of metabolism from genome data, analysis of enzyme deficiencies, and drug
target identification in metabolic networks.",
crossref
= "PMID:10700151",
}
@InProceedings{Salamonsenetal99,
author
= "W. Salamonsen and K. Y.
Mok and P. Kolatkar and S. Subbiah S",
title
= "BioJAKE: a tool for the
creation, visualization and manipulation of metabolic pathways",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "392--400",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Salamonsen.pdf",
keywords
= "visualization,
implementation, metabolism, BioJAKE, abstraction, type hierarchy,
database",
abstract
= "The BioJAKE program has been
created for the visualization, creation and manipulation of metabolic pathways.
It has been designed to provide a familiar and easy-to-use interface while
still allowing for the input and manipulation of complex and detailed metabolic
data. In recognition of the detailed and diverse sources of data available
across the Internet, it also provides a mechanism by which remote database
queries can be stored and performed with respect to individual molecules within
a pathway. This remote database access functionality is offered in addition to
comprehensive local database creation, management and querying capability. The
program has been developed in Java so as to provide for platform independence
and maximum extendibility.",
crossref
= "PMID:10380213",
}
@InProceedings{StapleyandBenoit00,
author
= "B. J. Stapley and G.
Benoit",
title
= "Biobibliometrics: information
retrieval and visualization from co-occurrences of gene names in Medline
abstracts",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "5",
pages
= "529--540",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/stapley.pdf",
keywords
= "visualization, literature,
NLP, biochemistry, information extraction, reconstruction,
implementation",
abstract
= "Successful information
retrieval from biomedical literature databases is becoming increasingly
difficult. We have developed a prototype system for retrieving and visualizing
information from literature and genomic databases using gene names. The premise
of our work is that, if two genes have a related biological function, the
co-occurrence of two gene names (or aliases of those genes) within the
biomedical literature is more likely. From a collection of Medline documents,
we have extracted the number of co-occurrences of every pair of Saccharomyces
cerevisiae genes. The query is automatically conflated to include gene aliases
as well. In addition, the retrieved document set can be filtered by the user
with a MeSH term. From this co-occurrence data we construct a matrix that
contains dissimilarity measurements of every pair of genes, based on their
joint and individual occurrence statistics. A graph is generated from this
matrix, with node and edge inclusion being determined by a user-defined
threshold. Nodes of the graph represent genes, while edge lengths are a
function of the occurrence of the two genes within the literature. Nodes can be
hypertext-linked to sequence databases, while edges are linked to those Medline
documents that generated them. The system is a tool for efficiently exploring
the biomedical information landscape and may act as a inference network.",
crossref
= "PMID:10902200",
}
@Article{SchwabandPienta97,
author
= "E. D. Schwab and K. J.
Pienta",
title
= "Modeling signal transduction
in normal and cancer cells using complex adaptive systems",
journal
= "Medical Hypotheses",
volume
= "48",
number
= "2",
pages
= "111--123",
year = "1997",
url = "",
keywords
= "signaling, Boolean network,
qualitative, logic, regulatory",
abstract
= "As a first approximation,
organisms can be defined by the complement of cell types that they possess.
Each cell type is defined by its specific collection of signal transduction
pathways. While many pathways are common to most cell types (e.g. glycolysis),
others are specific to a particular cell type and serve to characterized that
cell. Many diseases, including cancer, are characterized by aberrations in
general and specific signal-transduction pathways. These pathways are generally
intricate and not easily modeled. The formalism of complex adaptive system
theory, however, provides the tools by which these pathways can be
investigated. By modeling signal-transduction pathways from the viewpoint of
complex adaptive systems, a deeper understanding of their intricacies may
result. This could eventually lead to novel methods of therapeutic intervention
in diseases that arise from aberrant signal transduction.",
crossref
= "PMID:9076693",
}
@InProceedings{Szallasi99,
author
= "Z. Szallasi",
title
= "Genetic network analysis
in light of massively parallel biological data",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "5--16",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Szallasi.pdf",
keywords
= "Boolean network, stochastic,
reconstruction, regulatory",
abstract
= "Complementary DNA microarray
and high density oligonucleotide arrays opened the opportunity for massively
parallel biological data acquisition. Application of these technologies will
shift the emphasis in biological research from primary data generation to
complex quantitative data analysis. Reverse engineering of time-dependent
gene-expression matrices is amongst the first complex tools to be developed.
The success of reverse engineering will depend on the quantitative features of
the genetic networks and the quality of information we can obtain from
biological systems. This paper reviews how the (1) stochastic nature, (2) the
effective size, and (3) the compartmentalization of genetic networks as well as
(4) the information content of gene expression matrices will influence our
ability to perform successful reverse engineering.",
crossref
= "PMID:10380181",
}
@InProceedings{SzallasiandLiang98,
author
= "Z. Szallasi and S.
Liang",
title
= "Modeling the normal and neoplastic
cell cycle with "realistic Boolean genetic networks": their
application for understanding carcinogenesis and assessing therapeutic
strategies.",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "66--76",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/szallasi.pdf",
keywords
= "Boolean network, stochastic,
reconstruction, regulatory, biochemistry",
abstract
= "In this paper we show how
Boolean genetic networks could be used to address complex problems in cancer
biology. First, we describe a general strategy to generate Boolean genetic
networks that incorporate all relevant biochemical and physiological parameters
and cover all of their regulatory interactions in a deterministic manner.
Second, we introduce realistic Boolean genetic networks that produce time
series measurements very similar to those detected in actual biological
systems. Third, we outline a series of essential questions related to cancer
biology and cancer therapy that could be addressed by the use of realistic
Boolean genetic network modeling.",
crossref
= "PMID:9697172",
}
@InProceedings{SchulzeKremer97a,
author
= "S. Schulze-Kremer",
title
= "Adding semantics to
genome databases: towards an ontology for molecular biology",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "5",
pages
= "272--275",
year = "1997",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "http://igd.rz-berlin.mpg.de/~www/oe/ismb97.ps.gz",
keywords
= "ontology, database,
molecular",
abstract
= "Molecular biology has a
communication problem. There are many databases using their own labels and
categories for storing data objects and some using identical labels and
categories but with a different meaning. Conversely, one concept is often found
under different names. Prominent examples are the concepts "gene" and
"protein sequence" which are used with different semantics by major
international genomic and protein databases thereby making database integration
difficult and strenuous. This situation can only be improved by either defining
individual semantic interfaces between each pair of databases (complexity of
order n2) or by implementing one agreeable, transparent and computationally
tractable semantic repository and linking each database to it (complexity of
order n). Ontologies are one means to provide such semantic repository by
explicitly specifying the meaning of and relation between the fundamental
concepts in an application domain. Here, heuristics for building an ontology
and the upper level and a database branch of a prospective Ontology for
Molecular Biology are presented and compared to other ontologies with respect
to suitability for molecular biology",
crossref
= "PMID:9322049",
}
@InProceedings{SchulzeKremer97b,
author
= "S. Schulze-Kremer",
title
= "Integrating and
Exploiting Large-Scale, Heterogeneous and Autonomous Databases with an Ontology
for Molecular Biology",
booktitle
= "Molecular Bioinformatics, Sequence
Analysis - The Human Genome Project",
volume
= "",
pages
= "43--56",
year = "1997",
editor
= "R. Hofestaedt and H.
Lim",
publisher
= "Shaker Verlag",
address
= "Aachen",
url = "http://igd.rz-berlin.mpg.de/~www/oe/ics97.ps.gz",
keywords
= "ontology, database,
molecular",
abstract
= "Numerous genome projects
worldwide produce and gather gigabytes of sequence, structure, cellular,
metabolic and other types of information to be stored in a large number of
autonomous databases.In this context, supercomputers are used for sequence and
structure comparison of objects within one database. The task of searching for
common motifs and biologically related pieces of information in largescale,
heterogeneous databases is computationally even more expensive. Current
approaches require the preparation of a single data pool prior to analysis. The
immediate use of several heterogeneous and autonomous databases in molecular
biology is prohibited by a great heterogeneity on many levels, especially on
the semantic level of defining the meaning of database categories. Here,
molecular biology has a communication problem. For example, even fundamental
technical terms as ``gene'' and ``protein sequence'' are used inconsistently by
researchers and major international genomic and protein databases. This
situation can only be improved by either defining individual semantic
interfaces between each pair of databases (complexity of order n 2 ) or by
implementing one agreeable, transparent and computationally tractable semantic
repository and linking each database to it (complexity of order n). Ontologies
are one means to provide such semantic repository by explicitly specifying the
meaning of and relation between the fundamental concepts in an application
domain. Here, heuristics for building an ontology and the upper level and
database branch of a prospective Ontology for Molecular Biology are presented and
compared to other ontologies with respect to suitability for integrating a set
of heterogeneous and autonomous databases in molecular biology",
crossref
= "",
}
@InProceedings{SchulzeKremer98,
author
= "S. Schulze-Kremer",
title
= "Ontologies for molecular
biology",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "695--706",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/schulze-kremer.pdf",
keywords
= "ontology, database,
molecular",
abstract
= "Molecular biology has a
communication problem. There are many databases using their own labels and
categories for storing data objects and some using identical labels and
categories but with a different meaning. A prominent example is the concept
"gene" which is used with different semantics by major international
genomic databases. Ontologies are one means to provide a semantic repository to
systematically order relevant concepts in molecular biology and to bridge the
different notions in various databases by explicitly specifying the meaning of
and relation between the fundamental concepts in an application domain. Here,
the upper level and a database branch of a prospective ontology for molecular
biology (OMB) is presented and compared to other ontologies with respect to
suitability for molecular biology",
crossref
= "PMID:9697223",
}
@Article{Shymkoetal97,
author
= "R. M. Shymko and P. De Meyts and R. Thomas",
title
= "Logical analysis of
timing-dependent receptor signalling specificity: application to the insulin
receptor metabolic and mitogenic signalling pathways",
journal
= "Biochemical Journal",
volume
= "326",
number
= "2",
pages
= "463--469",
year = "1997",
url = "http://www.biochemj.org/bj/326/0463/3260463.pdf",
keywords
= "logic, signaling, analysis,
Boolean network, qualitative",
abstract
= "We present a method for
logical analysis of signal-transduction networks, focusing on metabolic and
mitogenic signalling by the insulin receptor, with specific emphasis on
dependence of the signalling properties on the timing of binding events. We
discuss a basic model which demonstrates this dependence (hormone binding leads
to activation of the receptor which can lead to a commitment to mitogenic
signalling), and show how residence time of the hormone on the receptor can
determine the specificity of signalling between the alternative metabolic or
mitogenic pathways. The method gives conditions for the selection of specific
branches in the signalling pathway expressed in terms of inequalities among the
characteristic activation or deactivation times of components of that pathway.
In this way, the conditions for mitogenic signaling can be given in terms of a
required range of values of the hormone residence time on the receptor, which is
directly related to the kinetic dissociation rate.",
crossref
= "PMID:9291119",
}
@Article{Sanchezetal97,
author
= "L. Sanchez and J. van
Helden and D. Thieffry",
title
= "Establishement of the
dorso-ventral pattern during embryonic development of drosophila melanogasater:
a logical analysis",
journal
= "Journal of Theoretical
Biology",
volume
= "189",
number
= "4",
pages
= "377--389",
year = "1997",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.1997.0523/pdf",
keywords
= "regulatory, analysis,
Boolean network, connectivity, systemic, spatial, feedback, qualitative",
abstract
= "This report focuses on
dorso-ventral patterning in the segmented region of the Drosophila melanogaster
embryo. According to the concept of positional information, this pattern
results from the different response of cells to the Dorsal-protein morphogen.
This protein shows a distribution gradient along the dorso-ventral axis, with
the highest concentration on the ventral side. Using the generalized logical
formalism developed by R. Thomas and co-workers, the different cellular
responses were analysed in terms of the intracellular loops between the
regulatory genes. Two positive loops were found to be involved, each
constituting a switch which can be acted upon by the Dorsal morphogen to
determine the different cell types that make up the embryonic dorso-ventral
pattern. The novelty in this use of generalized logical formalism is the
employment of a multilevel variable to represent a morphogen gradient. The
proposed model accounts for the essential qualitative effects of the Dorsal
gradient in the dorso-ventral determination process. Three main conclusions may
be drawn. Firstly, the gene twist needs to have two functional threshold
concentrations, one for autoactivation and the other for activation of the gene
snail. Secondly, the autoactivation threshold must be smaller than that which
activates snail. Thirdly, the action of the gene snail on the maintenance
function of the gene twist is crucial for cells to be able to choose between
the mesoderm or neuroectoderm developmental pathways. Furthermore, it is
predicted that if the gene snail shows autoregulation, this will not be crucial
for the determination of the embryonic D-V pattern.",
crossref
= "PMID:9446747",
}
@InProceedings{SamsonovaandSerov99,
author
= "M. G. Samsonova and V. N.
Serov",
title
= "NetWork: an interactive
interface to the tools for analysis of genetic network structure and
dynamics",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "102--111",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Samsonova.pdf",
keywords
= "implementation,
visualization, Boolean network, simulation, object-oriented, NetWork,
GeneGraph, graphical, GeNet, database",
abstract
= "We designed a Java applet
called NetWork which enables a user to interactively construct and visualize a
genetic network of interest, and to and to evaluate and explore its dynamics in
the framework of a Boolean network model. NetWork displays the mechanism of
gene interactions at the level of gene expression and enables the visualization
of large genetic networks. NetWork can serve as an interactive interface to
tools for the analysis of genetic network structure and behavior",
crossref
= "PMID:10380189",
}
@Article{Serovetal98,
author
= "V. N. Serov and A. V.
Spirov and M. G. Samsonova",
title
= "Graphical interface to
the genetic network database GeNet",
journal
= "Bioinformatics",
volume
= "14",
number
= "6",
pages
= "546--547",
year = "1998",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/14/6/546.pdf",
keywords
= "visualization, GeNet,
implementation, database, object-oriented, kinetic, graphical, regulatory,
biochemistry, signaling, equivalence, GeneGraph, GeNet",
abstract
= "SUMMARY: We designed a Java
applet which enables the visualization of genetic networks and can be used as a
Web publishing tool by molecular biologists studying the mechanisms of gene
interactions. AVAILABILITY: http://www.csa.ru/Inst/gorb_dep/inbios/
genet/Graph/Genes_Graph.html",
crossref
= "PMID:9694997",
}
@Article{Schaffetal00,
author
= "J. C. Schaff and B. M.
Slepchenko and L. M. Loew",
title
= "Physiological modeling
with virtual cell framework",
journal
= "Methods in Enzymology",
volume
= "321",
number
= "",
pages
= "1--23",
year = "2000",
url = "",
keywords
= "simulation, kinetic,
implementation, Virtual Cell, diffusion, spatial, image, biochemistry",
abstract
= "This article describes a
computational framework for cell biological modeling and simulation that is
based on the mapping of experimental biochemical and electrophysiological data
onto experimental images. The framework is designed to enable the construction
of complex general models that encompass the general class of problems coupling
reaction and diffusion.",
crossref
= "PMID:10909048",
}
@InProceedings{SchaffandLeow99,
author
= "J. C. Schaff and L. M.
Loew",
title
= "The virtual cell",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "228--239",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Schaff.pdf",
keywords
= "simulation, kinetic,
implementation, Virtual Cell, diffusion, spatial, image, biochemistry",
abstract
= "This paper describes a
computational framework for cell biological modeling and simulation that is
based on the mapping of experimental biochemical and electrophysiological data onto experimental images. The framework
is designed to enable the construction of complex general models that encompass
the general class of problems coupling reaction and diffusion.",
crossref
= "PMID:10380200",
}
@Article{Schaffetal97,
author
= "J. C. Schaff and C. C.
Fink and B. M. Slepchenko and J. H. Carson and L. M. Loew",
title
= "A general computational
framework for modeling cellular structure and function",
journal
= "Biophysical Journal",
volume
= "73",
number
= "3",
pages
= "1135--1146",
year = "1997",
url = "",
keywords
= "simulation, kinetic,
implementation, Virtual Cell, diffusion, spatial, image, biochemistry",
abstract
= "The "Virtual Cell"
provides a general system for testing cell biological mechanisms and creates a
framework for encapsulating the burgeoning knowledge base comprising the
distribution and dynamics of intracellular biochemical processes. It approaches
the problem by associating biochemical and electrophysiological data describing
individual reactions with experimental microscopic image data describing their
subcellular localizations. Individual processes are collected within a physical
and computational infrastructure that accommodates any molecular mechanism
expressible as rate equations or membrane fluxes. An illustration of the method
is provided by a dynamic simulation of IP3-mediated Ca2+ release from
endoplasmic reticulum in a neuronal cell. The results can be directly compared
to experimental observations and provide insight into the role of
experimentally inaccessible components of the overall mechanism.",
crossref
= "PMID:9284281",
}
@Article{Savageau91,
author
= "M. A. Savageau",
title
= "Biochemical systems
theory: operational differences among variant representations and their
significance.",
journal
= "Journal of Theoretical
Biology",
volume
= "151",
number
= "4",
pages
= "509-530",
year = "1991",
url = "",
keywords
= "kinetic, power-law
formalism, S-system, flux balancing, qualitative, analysis, metabolism,
systemic, metabolic control, biochemistry",
abstract
= "An appropriate language or
formalism for the analysis of complex biochemical systems has been sought for
several decades. The necessity for such a formalism results from the large
number of interacting components in biochemical systems and the complex
non-linear character of these interactions. The Power-Law Formalism, an example
of such a language, underlies several recent attempts to develop an
understanding of integrated biochemical systems. It is the simplest
representation of integrated biochemical systems that has been shown to be
consistent with well-known growth laws and allometric relationships--the most
regular, quantitative features that have been observed among the systemic
variables of complex biochemical systems. The Power-Law Formalism provides the
basis for Biochemical Systems Theory, which includes several different
strategies of representation. Among these, the synergistic-system (S-system)
representation is the most useful, as judged by a variety of objective
criteria. This paper first describes the predominant features of the S-system
representation. It then presents detailed comparisons between the S-system
representation and other variants within Biochemical Systems Theory. These
comparisons are made on the basis of objective criteria that characterize the
efficiency, power, clarity and scope of each representation. Two of the
variants within Biochemical Systems Theory are intimately related to other
approaches for analyzing biochemical systems, namely Metabolic Control Theory
and Flux-Oriented Theory. It is hoped that the comparisons presented here will
result in a deeper understanding of the relationships among these variants.
Finally, some recent developments are described that demonstrate the potential
for further growth of Biochemical Systems Theory and the underlying Power-Law
Formalism on which it is based.",
crossref
= "PMID:1943154",
}
@InProceedings{Savageau98,
author
= "M.A. Savageau",
title
= "Rules for the evolution
of gene circuitry",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "54--65",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/savageau.pdf",
keywords
= "regulatory, comparative,
analysis, kinetic, power-law formalism, mutation, qualitative,
quantitative",
abstract
= "Cells possess the genes
required for growth and function in a variety of contexts. In any given context
there is a corresponding pattern of gene expression in which some genes are OFF
and others ON. The ability of cells to switch genes ON and OFF in a coordinate
fashion to produce the required patterns of expression is the fundamental basis
for complex processes like normal development and pathogenesis. The molecular
study of gene regulation has revealed a plethora of mechanisms and circuitry
that have evolved to perform what appears to be the same switching function. To
some this implies the absence of rules. However, simple rules capable of
relating molecular design to the natural environment have begun to emerge
through the analysis of elementary gene circuits. Two of these rules are
reviewed in this paper. These simple rules have the ability to unify
understanding across several different levels of biological
organization--molecular, physiological, developmental, ecological.",
crossref
= "PMID:9697171",
}
@InCollection{Savageau96,
author
= "M. A. Savageau",
editor
= "J. Collado-Vides and B.
Magasanik and T. F. Smith",
booktitle
= "Integrative Approaches to
Molecular Biology",
title
= "A kinetic formalism for
integrative molecular biology: Manifestation in biochemical systems theory and
use in elucidating design principles for gene circuits",
publisher
= "The MIT Press",
address
= "Cambridge,
Massachusetts",
pages
= "115--146",
year = "1996",
}
@Article{Schillingetal99,
author
= "C. H. Schilling and S.
Schuster and B. O. Palsson and R. Heinrich",
title
= "Metabolic pathway
analysis: basic concepts and scientific applications in the post-genomic
era",
journal
= "Biotechnology
Progress",
volume
= "15",
number
= "3",
pages
= "296--303",
year = "1999",
url = "http://pubs.acs.org/isubscribe/journals/bipret/15/i03/pdf/bp990048k.pdf",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing,
phenotype phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, metabolic control",
abstract
= "This article reviews the
relatively short history of metabolic pathway analysis. Computer-aided
algorithms for the synthesis of metabolic pathways are discussed. Important
algebraic concepts used in pathway analysis, such as null space and convex
cone, are explained. It is demonstrated how these concepts can be translated
into meaningful metabolic concepts. For example, it is shown that the simplest
vectors spanning the region of all admissible fluxes in stationary states, for
which the term elementary flux modes was coined, correspond to fundamental
pathways in the system. The concepts are illustrated with the help of a
reaction scheme representing the glyoxylate cycle and adjacent reactions of
aspartate and glutamate synthesis. The interrelations between pathway analysis
and metabolic control theory are outlined. Promising applications for genome
annotation and for biotechnological purposes are discussed. Armed with a better
understanding of the architecture of cellular metabolism and the enormous
amount of genomic data available today, biochemists and biotechnologists will
be able to draw the entire metabolic map of a cell and redesign it by rational
and directed metabolic engineering.",
crossref
= "PMID:10356246",
}
@Article{Schillingetal99a,
author
= "C. H. Schilling and J. S.
Edwards and B. O. Palsson",
title
= "Toward metabolic
phenomics: analysis of genomic data using flux balances",
journal
= "Biotechnology
Progress",
volume
= "15",
number
= "3",
pages
= "288--295",
year = "1999",
url = "http://pubs.acs.org/isubscribe/journals/bipret/15/i03/pdf/bp9900357.pdf",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing,
phenotype phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative",
abstract
= "Small genome sequencing and
annotations are leading to the definition of metabolic genotypes in an
increasing number of organisms. Proteomics is beginning to give insights into
the use of the metabolic genotype under given growth conditions. These data
sets give the basis for systemically studying the genotype-phenotype
relationship. Methods of systems science need to be employed to analyze,
interpret, and predict this complex relationship. These endeavors will lead to
the development of a new field, tentatively named phenomics. This article
illustrates how the metabolic characteristics of annotated small genomes can be
analyzed using flux balance analysis (FBA). A general algorithm for the
formulation of in silico metabolic genotypes is described. Illustrative
analyses of the in silico Escherichia coli K-12 metabolic genotypes are used to
show how FBA can be used to study the capabilities of this strain.",
crossref
= "PMID:10356245",
}
@Article{SchillingandPalsson98,
author
= "C. H. Schilling and B. O.
Palsson",
title
= "The underlying pathway
structure of biochemical reaction networks",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "95",
number
= "8",
pages
= "4193--4198",
year = "1998",
url = "http://www.pubmedcentral.nih.gov/picrender.cgi?artid=6558&pictype=5",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing,
phenotype phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, mutation",
abstract
= "Bioinformatics is yielding
extensive, and in some cases complete, genetic and biochemical information
about individual cell types and cellular processes, providing the composition
of living cells and the molecular structure of its components. These components
together perform integrated cellular functions that now need to be analyzed. In
particular, the functional definition of biochemical pathways and their role in
the context of the whole cell is lacking. In this study, we show how the mass
balance constraints that govern the function of biochemical reaction networks
lead to the translation of this problem into the realm of linear algebra. The
functional capabilities of biochemical reaction networks, and thus the choices that
cells can make, are reflected in the null space of their stoichiometric matrix.
The null space is spanned by a finite number of basis vectors. We present an
algorithm for the synthesis of a set of basis vectors for spanning the null
space of the stoichiometric matrix, in which these basis vectors represent the
underlying biochemical pathways that are fundamental to the corresponding
biochemical reaction network. In other words, all possible flux distributions
achievable by a defined set of biochemical reactions are represented by a
linear combination of these basis pathways. These basis pathways thus represent
the underlying pathway structure of the defined biochemical reaction network.
This development is significant from a fundamental and conceptual standpoint
because it yields a holistic definition of biochemical pathways in contrast to
definitions that have arisen from the historical development of our knowledge
about biochemical processes. Additionally, this new conceptual framework will
be important in defining, characterizing, and studying biochemical pathways
from the rapidly growing information on cellular function.",
crossref
= "PMID:9539712",
}
@Article{SchillingandPalsson00,
author
= "C.H. Schilling and B. O.
Palsson",
title
= "Assessment of the
metabolic capabilities of Haemophilus influenzae Rd through a genome-scale
pathway analysis",
journal
= "Journal of Theoretical
Biology",
volume
= "203",
number
= "3",
pages = "249--283",
year = "2000",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.2000.1088/pdf",
keywords
= "data representation, kinetic,
algebraic, biochemistry, stoichiometry, analysis, flux balancing, phenotype
phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, mutation, modular",
abstract
= "The annotated full DNA sequence
is becoming available for a growing number of organisms. This information along
with additional biochemical and strain-specific data can be used to define
metabolic genotypes and reconstruct cellular metabolic networks. The first
free-living organism for which the entire genomic sequence was established was
Haemophilus influenzae. Its metabolic network is reconstructed herein and
contains 461 reactions operating on 367 intracellular and 84 extracellular
metabolites. With the metabolic reaction network established, it becomes
necessary to determine its underlying pathway structure as defined by the set
of extreme pathways. The H. influenzae metabolic network was subdivided into
six subsystems and the extreme pathways determined for each subsystem based on
stoichiometric, thermodynamic, and systems-specific constraints. Positive
linear combinations of these pathways can be taken to determine the extreme
pathways for the complete system. Since these pathways span the capabilities of
the full system, they could be used to address a number of important
physiological questions. First, they were used to reconcile and curate the
sequence annotation by identifying reactions whose function was not supported
in any of the extreme pathways. Second, they were used to predict gene products
that should be co-regulated and perhaps co-expressed. Third, they were used to
determine the composition of the minimal substrate requirements needed to
support the production of 51 required metabolic products such as amino acids,
nucleotides, phospholipids, etc. Fourth, sets of critical gene deletions from
core metabolism were determined in the presence of the minimal substrate
conditions and in more complete conditions reflecting the environmental niche
of H. influenzae in the human host. In the former case, 11 genes were
determined to be critical while six remained critical under the latter
conditions. This study represents an important milestone in theoretical
biology, namely the establishment of the first extreme pathway structure of a
whole genome.",
crossref
= "PMID:10716908",
}
@Article{Schillingetal00,
author
= "C. H. Schilling and D.
Letscher and B. O. Palsson",
title
= "Theory for the systemic
definition of metabolic pathways and their use in interpreting metabolic
function from a pathway-oriented perspective",
journal
= "Journal of Theoretical
Biology",
volume
= "203",
number
= "3",
pages
= "229--248",
year = "2000",
url = "http://www.idealibrary.com/links/doi/10.1006/jtbi.2000.1073/pdf",
keywords
= "data representation,
kinetic, algebraic, biochemistry, stoichiometry, analysis, flux balancing,
phenotype phase plane, metabolism, steady-state, whole genome, physicochemical
constraints, quantitative, qualitative, mutation, modular, extreme pathways,
pathway discovery, pathway classification",
abstract
= "Cellular metabolism is most
often described and interpreted in terms of the biochemical reactions that make
up the metabolic network. Genomics is providing near complete information
regarding the genes/gene products participating in cellular metabolism for a
growing number of organisms. As the true functional units of metabolic systems
are its pathways, the time has arrived to define metabolic pathways in the
context of whole-cell metabolism for the analysis of the structural design and
capabilities of the metabolic network. In this study, we present the
theoretical foundations for the identification of the unique set of
systemically independent biochemical pathways, termed extreme pathways, based
on system stochiometry and limited thermodynamics. These pathways represent the
edges of the steady-state flux cone derived from convex analysis, and they can
be used to represent any flux distribution achievable by the metabolic network.
An algorithm is presented to determine the set of extreme pathways for a system
of any complexity and a classification scheme is introduced for the
characterization of these pathways. The property of systemic independence is
discussed along with its implications for issues related to metabolic
regulation and the evolution of cellular metabolic networks. The underlying
pathway structure that is determined from the set of extreme pathways now
provides us with the ability to analyse, interpret, and perhaps predict
metabolic function from a pathway-based perspective in addition to the
traditional reaction-based perspective. The algorithm and classification scheme
developed can be used to describe the pathway structure in annotated genomes to
explore the capabilities of an organism.",
crossref
= "PMID:10716907",
}
@Article{Sauro93,
author
= "H. M. Sauro",
title
= "SCAMP: a general-purpose
simulator and metabolic control analysis program",
journal
= "Computer Applications in
Bioscience",
volume
= "9",
number
= "4",
pages = "441--450",
year = "1993",
url = "http://members.tripod.co.uk/sauro/biotech.htm",
keywords
= "kinetic, analysis, molecular
control, metabolism, implementation, biochemistry, simulation, scamp",
abstract
= "SCAMP is a general-purpose
simulator of metabolic and chemical networks. The program is written in C and
is portable to all computer systems that support an ANSI C compiler. SCAMP
accepts metabolic models described in a biochemical language, and this enables
novice as well as experienced users rapidly to build and simulate metabolic
systems. The language is sufficiently flexible to enable other types of model
to be built, e.g. chemostat or ecological models. The language offers many
facilities, including: the ability to describe metabolic pathways of any
structure and possessing any kinetics using normal chemical notation;
optionally build models directly from the differential equations; differing
compartment volumes; access to flux, concentration and rate of change
information; detection of conserved cycles; access to all coefficients and
elasticities of metabolic control analysis; user-defined forcing functions at
the model boundaries; user-defined monitoring functions; user-configurable
output of any quantity. From the model description SCAMP can either generate C
code for later compilation to produce fast executable stand-alone models or
run-time code for input to a run-time interpreter for immediate execution. The
simulator also incorporates an inbuilt symbolic differentiator for evaluating
the Jacobian and elasticity matrices",
crossref
= "PMID:8402211",
}
@Article{SimonShimizuetal00,
author
= "T. Simon-Shimizu and N.
Le-Novere and M. Daniel-Levin and A. J. Beavil and B. J. Sutton and D.
Bray",
title
= "Molecular model of a
lattice of signalling proteins involved in bacterial chemotaxis.",
journal
= "Nature Cell Biology",
volume
= "2",
number
= "11",
pages
= "792--796",
year = "2000",
keywords
= "kinetic, spatial, analysis,
signaling, biochemistry",
abstract
= "Coliform bacteria detect
chemical attractants by means of a membrane-associated cluster of receptors and
signalling molecules. We have used recently determined molecular structures, in
conjunction with plastic models generated by three-dimensional printer
technology, to predict how the proteins of the complex are arranged in relation
to the plasma membrane. The proposed structure is a regular two-dimensional
lattice in which the cytoplasmic ends of chemotactic-receptor dimers are
inserted into a hexagonal array of CheA and CheW molecules. This structure
creates separate compartments for adaptation and downstream signalling, and
indicates a possible basis for the spread of activity within the
cluster.",
crossref = "PMID:11056533",
}
@Article{Trankleetal00,
author
= "F. Trankle and M. Zeitz
and M. Ginkel and E.D. Gilles",
title = "PROMOT: A Modeling Tool for Chemical Processes",
journal
= "Mathematical and Computer
Modelling of Dynamical Systems",
volume
= "6",
number
= "3",
pages
= "283-307",
year = "2000",
url = "",
keywords
= "implemenation, PROMOT,
object-oriented, simulation, quantitative, kinetic, graphical, knowledge
representation",
abstract
= "The novel process modeling
tool PROMOT supports the object-oriented modeling of chemical processes for the
simulation environment DIVA. In PROMOT,
differential-algebraic
process models can be built by aggregating structural and behavioral modeling
entities that represent the topological structure or the dynamic and steady-state behavior, respectively, of the
investigated chemical processes. Process models and their modeling entities may
be defined either in an object-oriented modeling language
or with a graphical user interface. This paper discusses the modeling concept,
the modeling language, the knowledge representation aspects, and the
implementation of PROMOT.",
crossref
= "",
}
@Article{TanayandShamir,
author
= "A. Tanay and R.
Shamir",
title = "Computational expansion of genetic networks",
journal
= "Bioinformatics",
volume
= "17",
number
= "",
pages
= "S270--S278",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/screenpdf/17/suppl_1/S270",
keywords
= "regulatory, inference,
reconstruction, implementation, GENESYS, expansion, graph",
abstract
= "We present a new methodology
for computational analysis of gene and protein networks. The aim is to generate
new educated hypotheses on gene functions and on the logic of the biological
network circuitry, based on gene expression profiles. The framework supports
the incorporation of biologically motivated network constraints and rules to
improve specificity. Since current data is insufficient for de-novo
reconstruction, the method receives as input a known pathway core and suggests
likely expansions to it. Network modeling is combinatorial, yet data can be
probabilistic. At the heart of the approach are a fitness function which
estimates the quality of suggested network expansions given the core and the
data, and a specificity measure of the expansions. The approach has been
implemented in an interactive software tool called GENESYS. We report
encouraging results in preliminary analysis of yeast ergosterol pathway based
on transcription profiles. In particular, the analysis suggests a novel
ergosterol transcription factor.",
crossref
= "PMID:11473018",
}
@Article{ThattaiandvanOudenaarden01,
author
= "M.
Thattai and A. van Oudenaarden",
title = "Intrinsic noise in gene regulatory networks",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "98",
number
= "15",
pages
= "8614-=8619",
year = "2001",
url = "http://www.pnas.org/cgi/reprint/98/15/8614.pdf",
keywords
= "regulatory, analysis,
feedback, quantitative, continous, stochastic, kinetic, steady state",
abstract
= "Cells
are intrinsically noisy biochemical reactors: low reactant numbers can lead to
significant statistical fluctuations in molecule numbers and reaction rates.
Here we use an analytic model to investigate the emergent noise properties of
genetic systems. We find for a single gene that noise is essentially determined
at the translational level, and that the mean and variance of protein
concentration can be independently controlled. The noise strength immediately
following single gene induction is almost twice the final steady-state value.
We find that fluctuations in the concentrations of a regulatory protein can
propagate through a genetic cascade; translational noise control could explain
the inefficient translation rates observed for genes encoding such regulatory
proteins. For an autoregulatory protein, we demonstrate that negative feedback
efficiently decreases system noise. The model can be used to predict the noise
characteristics of networks of arbitrary connectivity. The general procedure is
further illustrated for an autocatalytic protein and a bistable genetic switch.
The analysis of intrinsic noise reveals biological roles of gene network
structures and can lead to a deeper understanding of their evolutionary origin.",
crossref
= "PMID:11438714",
}
@InProceedings{Tohsatoetal00,
author
= "Y. Tohsato and H. Matsuda
and A. Hashimoto",
title = "A multiple alignment algorithm for metabolic pathway analysis using enzyme hierarchy ",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "8",
pages
= "376--383",
year = "2000",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "ftp://ftp.sdsc.edu/pub/sdsc/biology/ISMB00/026.pdf",
keywords
= "metabolism, analysis, graph,
comparative, pathway alignment, qualitative",
abstract = "In many of the chemical reactions in living cells, enzymes act as catalysts in the conversion of certain compounds (substrates) into other compounds (products). Comparative analyses of the metabolic pathways formed by such reactions give important information on their evolution and on pharmacological targets (Dandekar et al. 1999). Each of the enzymes that constitute a pathway is classified according to the EC (Enzyme Commission) numbering system, which consists of four sets of numbers that categorize the type of the chemical reaction catalyzed. In this study, we consider that reaction similarities can be expressed by the similarities between EC numbers of the respective enzymes. Therefore, in order to find a common pattern among pathways, it is desirable to be able to use the functional hierarchy of EC numbers to express the reaction similarities. In this paper, we propose a multiple alignment algorithm utilizing information content that is extended to symbols having a hierarchical structure. The effectiveness of our method is demonstrated by applying the method to pathway analyses of sugar, DNA and amino acid metabolisms.",
crossref
= "PMID:10977098",
}
@InProceedings{Thomasetal00,
author
= "J. Thomas and D. Milward
and C. Ouzounis and S. Pulman and M. Carroll",
title
= "Automatic extraction of
protein interactions from scientific abstracts",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "5",
pages
= "541--552",
year = "2000",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb00/thomas.pdf",
keywords
= "implementation, Highlight,
literature, NLP, biochemistry, protein-protein, information extraction,
reconstruction, implementation",
abstract
= "This paper motivates the use
of Information Extraction (IE) for gathering data on protein interactions,
describes the customization of an existing IE system, SRI's Highlight, for this
task and presents the results of an experiment on unseen Medline abstracts
which show that customization to a new domain can be fast, reliable and
cost-effective.",
crossref
= "PMID:10902201",
}
@Article{Thomas91,
author
= "R. Thomas",
title
= "Regulatory metworks seen
as asynchronous automata: A logical description",
journal
= "Journal of Theoretical
Biology",
volume
= "153",
number
= "",
pages
= "1--23",
year = "1991",
url = "",
keywords
= "Boolean network, logic,
qualitative, regulatory, feedback, analysis, asynchronous, kinetic",
abstract
= "The aim of this paper is to
provide a compact answer to the questions: Why treat complex biological systems
in logical terms? How can one do it conveniently? Our initial description is
what we now call the "naive" logical description. After recalling the
essential elements of this asynchronous description, the present paper introduces:
the use of logical variables with more than two values; the notion of logical
parameters; the logical identification of all steady states of the differential
description; the notion of characteristic state of feedback loops; a compact
matricial presentation. This is an essentially methodological paper. More
extended developments including concrete biological examples will be found
elsewhere.",
crossref
= "",
}
@Article{ThieffryandRomero99,
author
= "D. Thieffry and D.
Romero",
title
= "The modularity of
biological regulatory networks",
journal
= "Biosystems",
volume
= "50",
number
= "1",
pages
= "49--59",
year = "1999",
url = "",
keywords
= "Boolean network, modular,
logic, qualitative, logical constraints, regulatory, feedback, analysis",
abstract
= "A useful approach to complex
regulatory networks consists of modeling their elements and interactions by
Boolean equations. In this context, feedback circuits (i.e. circular sequences
of interactions) have been shown to play key dynamical roles: whereas positive
circuits are able to generate multistationarity, negative circuits may generate
oscillatory behavior. In this paper, we principally focus on the case of gene
networks. These are represented by fully connected Boolean networks where each
element interacts with all elements including itself. Flexibility in network
design is introduced by the use of Boolean parameters, one associated with each
interaction or group of interactions affecting a given element. Within this
formalism, a feedback circuit will generate its typical dynamical behavior
(i.e. multistationarity or oscillations) only for appropriate values of some of
the logical parameters. Whenever it does, we say that the circuit is
'functional'. More interestingly, this formalism allows the computation of the
constraints on the logical parameters to have any feedback circuit functional
in a network. Using this methodology, we found that the fraction of the total
number of consistent combinations of parameter values that make a circuit
functional decreases geometrically with the circuit length. From a biological
point of view, this suggests that regulatory networks could be decomposed into
small and relatively independent feedback circuits or 'regulatory
modules'.",
crossref
= "PMID:10235650",
}
@InProceedings{ThieffryandThomas98,
author
= "D. Thieffry and R.
Thomas",
title
= "Qualitative analysis of gene networks",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "77--88",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/thieffry.pdf",
keywords
= "qualitative, implementation,
feedback, Boolean network, logic, analysis, asynchronous, kinetic logic,
regulatory",
abstract
= "In this paper, we review the
qualitative tools developed by our group for the analysis of regulatory
networks. Focusing on the dynamical and biological roles of feedback circuits,
this method can be applied in the context of both logical and differential
formalisms. This approach already led to several interesting results about the
relation between the network structure and the corresponding dynamical
properties. In particular, it could be shown that at least one positive
regulatory circuit is necessary to generate multistationarity (i.e.,
alternative states of gene expression), whereas at least one negative circuit
is necessary to generate a stable oscillatory behavior. Applications to the
analysis of complex gene networks, as well as to the synthesis of regulatory
models to account for global expression data are discussed.",
crossref
= "PMID:9697173",
}
@Article{Thieffryetal98,
author
= "D. Thieffry and A. M.
Huerta and E. Perez-Rueda and J. Collado-Vides",
title
= "From specific gene
regulation to genomic networks: a global analysis of transcriptional regulation
in Escherichia coli",
journal
= "Bioessays",
volume
= "20",
number
= "5",
pages
= "433--440",
year = "1998",
url = "http://www3.interscience.wiley.com/cgi-bin/fulltext?ID=34255&PLACEBO=IE.pdf",
keywords
= "regulatory, analysis,
Boolean network, connectivity, systemic",
abstract
= "Because a large number of
molecular mechanisms involved in gene regulation have been described during the
last decades, it is now becoming possible to address questions about the global
structure of gene regulatory networks, at least in the case of some of the
best-characterized organisms. This paper presents a global characterization of
the transcriptional regulation in Escherichia coli on the basis of the current
data. The connectivity of the corresponding network was evaluated by analyzing
the distribution of the number of genes regulated by a given regulatory
protein, and the distribution of the number of regulatory genes regulating a
given regulated gene. The mean connectivity found (between 2 and 3) shows a
rather loosely interconnected structure. Special emphasis is given to circular
sequences of interactions ("circuits") because of their critical
dynamical properties. Only one-element circuits were found, in which negative
autoregulation is the dominant architecture. These global properties are
discussed in light of several pertinent theoretical approaches, as well as in terms
of physiological and evolutionary considerations.",
crossref
= "PMID:9670816",
}
@Article{Tomitaetal99,
author
= "M. Tomita and K. Hashimoto
and K. Takahashi and T. S. Shimizu and Y. Matsuzaki and F. Miyoshi and K. Saito
and S. Tanida and K. Yugi and J. C. Venter and C. A. Hutchison 3rd",
title
= "E-CELL: software
environment for whole-cell simulation",
journal
= "Bioinformatics",
volume
= "15",
number
= "1",
pages
= "72--84",
year = "1999",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/15/1/72.pdf",
keywords
= "simulation, implementation, kinetic,
object-oriented, spatial,E-cell",
abstract
= "MOTIVATION: Genome
sequencing projects and further systematic functional analyses of complete gene
sets are producing an unprecedented mass of molecular information for a wide
range of model organisms. This provides us with a detailed account of the cell
with which we may begin to build models for simulating intracellular molecular
processes to predict the dynamic behavior of living cells. Previous work in
biochemical and genetic simulation has isolated well-characterized pathways for
detailed analysis, but methods for building integrative models of the cell that
incorporate gene regulation, metabolism and signaling have not been
established. We, therefore, were motivated to develop a software environment
for building such integrative models based on gene sets, and running
simulations to conduct experiments in silico. RESULTS: E-CELL, a modeling and
simulation environment for biochemical and genetic processes, has been
developed. The E-CELL system allows a user to define functions of proteins,
protein-protein interactions, protein-DNA interactions, regulation of gene
expression and other features of cellular metabolism, as a set of reaction
rules. E-CELL simulates cell behavior by numerically integrating the
differential equations described implicitly in these reaction rules. The user
can observe, through a computer display, dynamic changes in concentrations of
proteins, protein complexes and other chemical compounds in the cell. Using
this software, we constructed a model of a hypothetical cell with only 127
genes sufficient for transcription, translation, energy production and
phospholipid synthesis. Most of the genes are taken from Mycoplasma genitalium,
the organism having the smallest known chromosome, whose complete 580 kb genome
sequence was determined at TIGR in 1995. We discuss future applications of the
E-CELL system with special respect to genome engineering. AVAILABILITY: The
E-CELL software is available upon request. SUPPLEMENTARY INFORMATION: The
complete list of rules of the developed cell model with kinetic parameters can
be obtained via our web site at: http://e-cell.org/.",
crossref
= "PMID:10068694",
}
@InProceedings{Thieffryetal97,
author
= "D. Thieffry and D.A.
Rosenblueth and A.M. Huerta and H. Salgado and J. Collado-Vides",
title
= "Definite-clause Grammars
for the Analysis of cis-Regulatory Regions in E.Coli",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "2",
pages
= "441--452",
year = "1997",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www-smi.stanford.edu/people/altman/psb97/thieffry.pdf",
keywords
= "logic, grammar, DNA
regulatory elements, prolog, qualitative",
abstract = "Based on an extensive collection of s70 associated regulatory mechanisms, a grammatical model has been constructed that define the functional positions and combinations of sites within DNA regulatory regions. The syntactic rules and the dictionary implemented in a Prolog program were coupled to consensus matrices used as "sensors" to integrate a syntactic recognizer. A systematic comparison between the syntactic recognizer and the standard weight matrix methodology is presented using 12 regulatory proteins and the whole collection of about 130 s70 DNA regulatory regions. On the average an increased sensitivity of 5 to 10 fold is obtained with this novel approach.",
crossref
= "PMID: 9390313",
}
@Article{VoitandRadivoyevitch00,
author
= "E. O. Voit and T.
Radivoyevitch",
title = "Biochemical systems analysis of genome-wide
expression data",
journal
= "Bioinformatics",
volume
= "16",
number
= "11",
pages
= "1023--1037",
year = "2000",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/16/11/1023.pdf",
keywords
= "kinetic, analysis, metabolism,
quantitative, steady state, S-system, PLAS, implementation, metabolic control,
flux balancing, power-law formalism, numerical, systemic",
abstract
= "Motivation: Modern methods
of genomics have produced an unprecedented amount of raw data. The
interpretation and explanation of these data constitute a major,
well-recognized challenge. Results: Biochemical Systems Theory (BST) is the
mathematical basis of a well-established methodological framework for analyzing
networks of biochemical reactions. An existing BST model of yeast glycolysis is
used here to explain and interpret the glycolytic gene expression pattern of
heat shocked yeast. Our analysis demonstrates that the observed gene expression
profile satisfies the primary goals of increased ATP, trehalose, and NADPH
production, while maintaining intermediate metabolites at reasonable levels.
Based on a systematic exploration of alternative, hypothetical expression
profiles, we show that the observed profile outperforms other profiles. Conclusion:
BST is a useful framework for combining DNA microarray data with enzymatic
process information to yield new insights into metabolic pathway regulation.
Availability: All analyses were executed with the software PLAS©, which is
freely available at http://correio.cc.fc.ul.pt/~aenf/plas.html for academic
use.",
crossref
= "PMID:11159314",
}
@InProceedings{vanSomerenetal00,
author
= "E. P. van Someren and L.
F. Wessels and M. J. Reinders",
title
= "Linear modeling of genetic networks from experimental
data",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "8",
pages
= "355--366",
year = "2000",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "ftp://ftp.sdsc.edu/pub/sdsc/biology/ISMB00/039.pdf",
keywords
= "linear, kinetic,
reconstruction, regulatory",
abstract
= "In this paper, the
regulatory interactions between genes are modeled by a linear genetic network
that is estimated from gene expression data. The inference of such a genetic
network is hampered by the dimensionality problem. This problem is inherent in
all gene expression data since the number of genes by far exceeds the number of
measured time points. Consequently, there are infinitely many solutions that
fit the data set perfectly. In this paper, this problem is tackled by combining
genes with similar expression profiles in a single prototypical 'gene'. Instead
of modeling the genes individually, the relations between prototypical genes
are modeled. In this way, genes that cannot be distinguished based on their
expression profiles are grouped together and their common control action is
modeled instead. This process reduces the number of signals and imposes a
structure on the model that is supported by the fact that biological genetic
networks are thought to be redundant and sparsely connected. In essence, the
ambiguity in model solutions is represented explicitly by providing a
generalized model that expresses the basic regulatory interactions between
groups of similarly expressed genes. The modeling approach is illustrated on
artificial as well as real data.",
crossref
= "PMID:10977096",
}
@Article{vanHeldenetal00,
author
= "J. van Helden and A. Naim
and R. Mancuso and M. Eldridge and L. Wernisch and D. Gilbert D and S. J.
Wodak",
title
= "Representing and
analysing molecular and cellular function using the computer",
journal
= "Biological Chemistry",
year = "2000",
volume
= "381",
number
= "9--10",
pages
= "921--935",
url = "http://www.degruyter.de/journals/bc/2000/pdf/381_921.pdf",
keywords
= "ontology, knowledge
representation, database, implementation, aMAZE, metabolism, signaling,
regulatory, visualization, pathway discovery, object-oriented,
compartment",
abstract
= "Determining the biological
function of a myriad of genes, and understanding how they interact to yield a
living cell, is the major challenge of the post genome-sequencing era. The
complexity of biological systems is such that this cannot be envisaged without
the help of powerful computer systems capable of representing and analysing the
intricate networks of physical and functional interactions between the
different cellular components. In this review we try to provide the reader with
an appreciation of where we stand in this regard. We discuss some of the
inherent problems in describing the different facets of biological function,
give an overview of how information on function is currently represented in the
major biological databases, and describe different systems for organising and
categorising the functions of gene products. In a second part, we present a new
general data model, currently under development, which describes information on
molecular function and cellular processes in a rigourous manner. The model is
capable of representing a large variety of biochemical processes, including
metabolic pathways, regulation of gene expression and signal transduction. It
also incorporates taxonomies for categorising molecular entities, interactions
and processes, and it offers means of viewing the information at different
levels of resolution, and dealing with incomplete knowledge. The data model has
been implemented in the database on protein function and cellular processes
'aMAZE' (http://www.ebi.ac.uk/research/pfbp/), which presently covers metabolic
pathways and their regulation. Several tools for querying, displaying, and
performing analyses on such pathways are briefly described in order to
illustrate the practical applications enabled by the model.",
crossref = "PMID:11076023",
}
@Article{vanHeldenetal01,
author = "J. van Helden and A. Naim and C. Lemer and R. Mancuso and M. Eldridge and S. Wodak",
title = "From molecular activities and processes to biological function",
journal
= "Briefings in
Bioinformatics",
volume
= "",
number
= "",
pages
= "",
note = "in press",
year = "2001",
url = "http://www.ebi.ac.uk/research/pfbp/publications/briefings_bioinfo_2001_preprint.pdf",
keywords
= "database, signaling,
ontology, implementation, aMAZE, metabolism, regulatory, compartment,
transport, modular, data representation, ontology, UML, object-oriented",
abstract
= "This paper describes how
biological function can be represented in terms of molecular activities and processes.
It presents several key features of a data model that is based on a conceptual
description of the network of interactions between molecular entities within
the cell and between cells. This model is implemented in the aMAZE database
that presently deals with information on metabolic pathways, gene regulation,
sub- or supra-cellular locations, and transport. We show that this model
constitutes a useful generalisation of data representations currently
implemented in metabolic pathway databases, and that it can furthermore include
multiple schemes for categorising and classifying molecular entities,
activities, processes and localisations. In particular, we highlight the
flexibility offered by our system in representing multiple molecular activities
and their control, in viewing biological function at different levels of
resolution and in updating this view as our knowledge evolves. The aMAZE
project Web site is at http://www.ebi.ac.uk/research/pfbp/",
crossref = "",
}
@Article{WojcikandSchachter01,
author = "J. Wojcik and V. Schachter",
title = "Protein-protein interaction map inference using interacting domain profile pairs",
journal
= "Bioinformatics",
volume
= "17",
number
= "",
pages
= "S296--S305",
year = "2001",
url = "http://bioinformatics.oupjournals.org/cgi/reprint/17/suppl_1/S296.pdf",
keywords
= "protein-protein, graph,
whole genome, reconstruction, inference, comparative, qualitative,
implementation, PIMRider",
abstract
= "A
number of predictive methods have been designed to predict protein interaction
from sequence or expression data. On the experimental front, however,
high-throughput proteomics technologies are starting to yield large volumes of
protein-protein interaction data. High-quality experimental protein interaction
maps constitute the natural dataset upon which to build interaction
predictions. Thus the motivation to develop the first interaction-based protein
interaction map prediction algorithm. A technique to predict protein-protein
interaction maps across organisms is introduced, the 'interaction-domain pair
profile' method. The method uses a high-quality protein interaction map with
interaction domain information as input to predict an interaction map in
another organism. It combines sequence similarity searches with clustering
based on interaction patterns and interaction domain information. We apply this
approach to the prediction of an interaction map of Escherichia coli from the
recently published interaction map of the human gastric pathogen Helicobacter
pylori. Results are compared with predictions of a second inference method
based only on full-length protein sequence similarity - the "naive"
method. The domain-based method is shown to i) eliminate a significant amount
of false-positives of the naive method that are the consequences of
multi-domain proteins; ii) increase the sensitivity compared to the naive
method by identifying new potential interactions. Availability: Contact the
authors.",
crossref
= "PMID:11473021",
}
@Article{WagnerandFell00a,
author
= "A. Wagner and D. A. Fell
",
title = "The Small World Inside Large Metabolic
Networks",
journal
= "Proceedings of the Royal
Society series B",
volume
= "",
number
= "",
pages
= "",
note = "submitted"
year = "2000",
url = "http://www.santafe.edu/sfi/publications/Working-Papers/00-07-041.pdf",
keywords
= "metabolism, analysis, small
world, graph, quantitative, connectivity",
abstract
= "We analyze the structure of
a large metabolic network, that of the energy and biosynthesis metabolism of Escherichia
coli. This network is a paradigmatic case for the large genetic and
metabolic networks that functional genomics efforts are beginning to elucidate.
To analyze the structure of networks involving hundreds or thousands of
components by simple visual inspection is impossible, and a quantitative
framework is needed to analyze them. We propose a graph theoretical description
of the E. coli metabolic network, a description that we hope will prove
useful for other genetic networks. We find that this network is a small world
graph, a type of graph observed in a variety of seemingly unrelated areas, such
as friendship networks in sociology, the structure of electrical power grids,
and the nervous system of C. elegans. Moreover, its connectivity follows
a power law, another unusual but by no means rare statistical distribution.
This architecture may serve to minimize transition times between metabolic
states, and also reflect the evolutionary history of metabolism. ",
crossref
= "",
}
@Unpublished{White00,
author = "B. White ",
title = "BioQUEST metabolic
pathways/enzyme kinetics simulation",
year = "2000",
url = "http://omega.cc.umb.edu/~bwhite/ek.html",
keywords
= "implementation, simulation,
BioQUEST, metabolism, kinetic",
abstract
= "Metabolic Pathways is a set
of building blocks that run on the numerical simulation program Extend. They
allow the user to construct model of uncatalyzed and catalyzed reactions and to
model the flows of reactants and products over time.",
crossref
= "",
}
@InProceedings{Wong01,
author
= "L. Wong",
title
= "PIES, A Protein
Interaction Extraction System",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "6",
pages
= "520--531",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/wong.pdf",
keywords
= "implementation, BioNLP,
Graphviz, visualization, database, NLP, literature, information extraction,
protein-protein",
abstract
= "We consider the problem of
extracting, manipulating, and managing biological pathways, especially
protein-protein interaction pathways. We discuss here the Protein Interaction
Extraction System (PIES). PIES is contructed on top of three main technologies:
Kleisli, BioNLP, and Graphviz. Kleisli is a broad-scale data integration system
that we use for downloading Medline abstracts and for general manipulation and
management of pathway/interaction databases. BioNLP is a natural language-based
information extraction module that we use for analyzing Medline abstracts and
to extract precise protein-protein and other interaction information. Graphviz
is a graphical layout package developed for directed graphs that we use for
visualization of the extracted pathways. PIES can be augmented with various
means for extracting protein interaction information from sequence databases,
for example, by using Kleisli's power to integrate sequence comparison tools to
detect gene fusion events in sequence databases.",
crossref
= "",
}
@InProceedings{Wesselsetal01,
author
= "L.F.A. Wessels and E.P.
Van Someren and M.J.T. Reinders",
title
= "A Comparison of Genetic
Network Models",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "6",
pages
= "508--519",
year = "2001",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb01/wessels.pdf",
keywords
= "reconstruction, Boolean
network, correlation metric construction, activation-inhibition network,
linear, steady state, robustness, stability, analysis, inference",
abstract
= "With the completion of the
sequencing of the human genome, the need for tools capable of unraveling the
interaction and functionality of genes becomes extremely urgent. In answer to
this quest, the advent of microarray technology provides the opportunity to
perform large scale gene expression analyses. Recently, genetic networks were
proposed as a possible methodology for modeling genetic interactions. Since
then, a wide variety of different models have been introduced. However, it is,
in general, unclear what the strengths and weaknesses of each of these
approaches are and where these models overlap and differ. This paper compares
different genetic modeling approaches that attempt to extract the gene
regulation matrix from expression data. A taxonomy of continuous genetic
network models is proposed and the following important characteristics are
suggested and employed to compare the models: (1) inferential power; (2)
predictive power; (3) robustness; (4) consistency; (5) stability and (6)
computational cost. Where possible, synthetic time series data are employed to
investigate some of these properties.",
crossref
= "",
}
@InProceedings{Weaveretal99,
author
= "D. C. Weaver and C. T.
Workman and G. D. Stormo",
title
= "Modeling regulatory
networks with weight matrices",
booktitle = "Pacific Symposium on
Biocomputing",
volume
= "4",
pages
= "112--123",
year = "1999",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb99/Weaver.pdf",
keywords
= "linear, reconstruction,
regulatory",
abstract
= "Systematic gene expression
analyses provide comprehensive information about the transcriptional response
to different environmental and developmental conditions. With enough gene
expression data points, computational biologists may eventually generate
predictive computer models of transcription regulation. Such models will
require computational methodologies consistent with the behavior of known
biological systems that remain tractable. We represent regulatory relationships
between genes as linear coefficients or weights, with the "net"
regulation influence on a gene's expression being the mathematical summation of
the independent regulatory inputs. Test regulatory networks generated with this
approach display stable and cyclically stable gene expression levels, consistent
with known biological systems. We include variables to model the effect of
environmental conditions on transcription regulation and observed various
alterations in gene expression patterns in response to environmental input.
Finally, we use a derivation of this model system to predict the regulatory
network from simulated input/output data sets and find that it accurately
predicts all components of the model, even with noisy expression data.",
crossref
= "PMID:10380190",
}
@InProceedings{Wuensche98,
author
= "A. Wuensche",
title
= "Genomic regulation
modeled as a network with basins of attraction",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "3",
pages
= "89--102",
year = "1998",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "http://www.smi.stanford.edu/projects/helix/psb98/wuensche.pdf",
keywords
= "Boolean network,
synchronous, simulation, implementation, DDLab",
abstract
= "Many natural processes
consist of networks of interacting elements which affect each other's state
over time, the dynamics depending on the pattern of connections and the
updating rules for each element. Genomic regulatory networks are arguably
networks of this sort. An attempt to understand genomic networks would benefit
from the context of a general theory of discrete dynamical networks which is
currently emerging. A key notion here is global dynamics, whereby state-space
is organized into basins of attraction, objects that have only recently become
accessible by computer simulation of idealized models, in particular
"random Boolean networks". Cell types have been explained as
attractors in genomic networks, where the network architecture is biased to
achieve a balance between stability and adaptability in response to
perturbation. Based on computer simulations using the software Discrete
Dynamics Lab (DDLab), these ideas are described, as well as order-chaos
measures on typical trajectories that further characterize network dynamics.",
crossref = "PMID:9697174",
}
@InProceedings{WaggandSellers97,
author
= "J. Wagg and P.
Sellers",
title
= "Enumeration of flux
routes through complex biochemical reactions",
booktitle
= "Pacific Symposium on
Biocomputing",
volume
= "2",
pages
= "453--464",
year = "1997",
editor
= "R. B. Altman and A. K.
Dunker and L. Hunter and T. E. Klein",
publisher
= "World Scientific Press",
address
= "Singapore",
url = "",
keywords
= "biochemistry, kinetics,
quantitative, flux route, simulation, steady state",
abstract
= "In the present work, a
general algorithm for enumeration of the flux routes via which a chemical
species "flows" through a complex biochemical reaction is outlined
and presented by way of a biological example, a kinetic model for potassium ion
permeation through a voltage-gated ion channel. The algorithm is readily
amenable to computer based implementation and when used in conjunction with an
existing algorithm provides a convenient means for simulation of the
equilibrium and steady-state isotope exchange kinetics of complex biochemical
reactions.",
crossref
= "PMID: 9390314",
}
@Article{WaggandChapman95,
author
= "J. Wagg and J. B.
Chapman",
title
= "Steady-state flux ratio
analysis: application to biological transport",
journal
= "Journal of Theoretical
Biology",
volume
= "174",
number
= "1",
pages
= "61--72",
year = "1995",
url = "http://www.idealibrary.com/links/artid/jtbi.1995.0078/production/pdf",
keywords
= "biochemistry, kinetics, quantitative, flux route, steady
state, analysis",
abstract
= "A thermodynamically
constrained method of flux ratio analysis, based upon a previously developed
thermodynamic rate ratio equation has been developed. In this paper it is
demonstrated that, for a complex reaction, application of the thermodynamic
rate ratio equation may provide a useful tool for the interpretation of
unidirectional flux data thought to be mediated by the reaction, provided that:
(i) a clearly defined mechanism for the reaction has been proposed; (ii) a set
of partial reaction components may be defined for the reaction from the
proposed mechanism, with the rate ratio of at least one of these components
being amenable to experimental measurement. This paper defines the conditions
for which the rate ratio of a component reaction may be measured, and
illustrates the basic principles underlying this approach to flux ratio
analysis by direct application to a number of hypothetical mechanisms for
biological transport phenomena.",
crossref
= "PMID:7643606",
}
@Article{Wagg87,
author
= "J. Wagg",
title
= "A method for defining
steady-state unidirectional fluxes through branched chemical, osmotic and
chemiosmotic reactions",
journal
= "Journal of Theoretical
Biology",
volume
= "128",
number
= "3",
pages
= "375--385",
year = "1987",
url = "",
keywords
= "biochemistry, kinetics, quantitative,
flux route, steady state, analysis",
abstract
= "A general mathematical
technique is described for deriving analytical expressions and obtaining
numerical solutions for the steady-state unidirectional fluxes between two
chemical states via any set of intermediate states present within any
hypothetical system of unbranched or branched and overlapping elementary
processes. The technique is a restricted application of the theory of Markov
processes with conditional probabilities being assigned to the chemical state
transitions constituting the system of reactions. While, in principle, the
technique requires the summation of an infinite power series of a matrix
defining the conditional probabilities of single state transitions, the power series
is evaluated by means of the Taylor series expansion for matrices. As this
technique allows isotopic exchange velocity equations to be derived from
systems of reactions in which no distinction between the labelled and
unlabelled species is required it provides a distinct and independent
alternative to previously proposed methods. The technique is illustrated by
application to a mechanism for second-order carrier-mediated transport.",
crossref
= "PMID:3444343",
}
@Article{Wingenderetal01,
author
= "E. Wingender and X. Chen
and E. Fricke and R. Geffers and R. Hehl and I. Liebich and M. Krull M and V.
Matys and H. Michael and R. Ohnhauser and M. Pruss and F. Schacherer and S.
Thiele and S. Urbach",
title
= "The TRANSFAC system on
gene expression regulation",
journal
= "Nucleic Acids
Research",
year = "2001",
volume
= "29",
number
= "1",
pages
= "281--283",
url = "http://nar.oupjournals.org/cgi/reprint/29/1/281.pdf",
keywords
= "database, graphical,
signaling, regulatory, visualization, object-oriented, implementation,
TRANSPATH, TRANSFAC, compartment",
abstract = "The TRANSFAC database on
transcription factors and their DNA-binding sites and profiles
(http://www.gene-regulation.de/) has been quantitatively extended and
supplemented by a number of modules. These modules give information about
pathologically relevant mutations in regulatory regions and transcription
factor genes (PathoDB), scaffold/matrix attached regions (S/MARt DB), signal
transduction (TRANSPATH) and gene expression sources (CYTOMER). Altogether,
these distinct database modules constitute the TRANSFAC system. They are
accompanied by a number of program routines for identifying potential
transcription factor binding sites or for localizing individual components in
the regulatory network of a cell.",
crossref
= "PMID:11125113",
}
@Article{Xenariosetal01,
author = "I. Xenarios and E. Fernandez E and L. Salwinski and X. J. Duan and M. J. Thompson and E. M. Marcotte and D. Eisenberg",
title = "DIP: the database of interacting proteins: 2001
update ",
journal
= "Nucleic Acids
Research",
volume
= "29",
number
= "1",
pages
= "239--241",
year = "2001",
url = "http://nar.oupjournals.org/cgi/reprint/29/1/239.pdf",
keywords
= "protein-protein, database,
visualization, graphical, comparative, implementation, DIP, molecular, domain,
literature, information extraction",
abstract
= "The Database of Interacting
Proteins (DIP; http://dip.doe-mbi.ucla. edu) is a database that documents
experimentally determined protein-protein interactions. Since January 2000 the
number of protein-protein interactions in DIP has nearly tripled to 3472 and
the number of proteins to 2659. New interactive tools have been developed to
aid in the visualization, navigation and study of networks of protein
interactions.",
crossref
= "PMID:11125102",
}
@Article{Xenariosetal00,
author = "I. Xenarios and D. W. Rice and L. Salwinski and M. K. Baron and E. M. Marcotte and D. Eisenberg",
title = "DIP: the database of interacting proteins",
journal
= "Nucleic Acids
Research",
volume
= "28",
number
= "1",
pages = "289--291",
year = "2000",
url = "http://nar.oupjournals.org/cgi/reprint/28/1/289.pdf",
keywords
= "protein-protein, database,
visualization, graphical, comparative, implementation, DIP, molecular, domain,
literature, information extraction",
abstract
= " The Database of Interacting
Proteins (DIP; http://dip.doe-mbi.ucla.edu) is a database that documents
experimentally determined protein-protein interactions. This database is
intended to provide the scientific community with a comprehensive and
integrated tool for browsing and efficiently extracting information about
protein interactions and interaction networks in biological processes. Beyond
cataloging details of protein-protein interactions, the DIP is useful for
understanding protein function and protein-protein relationships, studying the
properties of networks of interacting proteins, benchmarking predictions of
protein-protein interactions, and studying the evolution of protein-protein
interactions.",
crossref
= "PMID:10592249",
}
@Article{Yietal00,
author
= "T-M. Yi and Y. Huang and
M. I. Simon and J. Doyle",
title
= "Robust perfect adaptation
in bacterial chemotaxis through integral feedback control",
journal
= "Proceedings of the National
Academy of Sciences USA",
volume
= "97",
number
= "9",
pages
= "4649--4653",
year = "2000",
url = "http://www.pnas.org/cgi/reprint/97/9/4649.pdf?ijkey=Vs0lbx6sGGNvg",
keywords
= "analysis, kinetic,
biochemical, signaling, modular",
abstract
= "Integral feedback control is a basic engineering strategy
for ensuring that the output of a system robustly tracks its desired value
independent of noise or variations in system parameters. In biological systems,
it is common for the response to an extracellular stimulus to return to its
prestimulus value even in the continued presence of the signal-a process termed
adaptation or desensitization. Barkai, Alon, Surette, and Leibler have provided
both theoretical and experimental evidence that the precision of adaptation in
bacterial chemotaxis is robust to dramatic changes in the levels and kinetic
rate constants of the constituent proteins in this signaling network [Alon, U.,
Surette, M. G., Barkai, N. & Leibler, S. (1998) Nature (London) 397, 168-171].
Here we propose that the robustness of perfect adaptation is the result of this
system possessing the property of integral feedback control. Using techniques
from control and dynamical systems theory, we demonstrate that integral control
is structurally inherent in the Barkai-Leibler model and identify and
characterize the key assumptions of the model. Most importantly, we argue that
integral control in some form is necessary for a robust implementation of
perfect adaptation. More generally, integral control may underlie the
robustness of many homeostatic mechanisms.",
crossref
= "PMID:10781070",
}
@InProceedings{ZaunerandConrad98,
author
= "K. P. Zauner and M.
Conrad",
title
= "Simulation experiments on
the role of spatial arrangement in enzymatic networks ",
booktitle
= "Modeling and Simulation of
Gene and Cell Regulation and Metabolic Pathways ",
Series
= "IBFI
Dagstuhl-Seminar-Report",
volume
= "215",
pages
= "44--46",
year = "1998",
editor
= "J. Collades-Vides and R.
Hofestädt and M. Marvrovouniotis and G. Michal",
publisher
= "",
address
= "",
url = "http://wwwiti.cs.uni-magdeburg.de/iti_bm/dagstuhl/",
keywords
= "simulation, implementation,
metabolism, biochemistry, kinetic, structure, spatial, conformation,
CKSD",
abstract = "Biochemical networks depend on an intricate interplay of conformation, kinetic, structural, and (molecular) dynamic factors. We have developed a simulation system that abstracts this interplay. The simulator provides a theoretical laboratory for investigating the role of dynamically changing structures in biomolecular information processing and control. Macromolecules and various small molecules (and ions) are represented in a 3Dsimulation space. The macromolecules can act catalytically on the small molecules in their local environment. They may also interact through attractive or repulsive forces with other macromolecules in their vicinity. The force (or dynamic) interactions and the catalytic properties of each of the macromolecules is dependent on its conformational state. Macromolecules are represented by dodecahedra, each of whose twelve faces is a finite automaton. The states of this compound finite automaton represent the conformational states of the macromolecule. The state transitions depend on the local milieu and on the state of neighboring macromolecules. The whole system forms a loop: conformation controls binding and catalytic interactions that influence supramolecular structure and chemical milieu. Structure and chemical milieu in turn influence conformation. The simulator was used to study a network composed of five types of enzymes with two competitive paths. The enzymes were represented by 3300 localized dodecahedra placed in a 1¯m 3 simulation space. The kinetic parameters and the number of enzymes of each type were chosen to be symmetrical for both of the competitive paths. The flux through these paths can be modulated by changing the relative spatial distribution of the enzymes in the simulation space. The results, in the case under consideration, demonstrate that the steady state concentrations of the milieu components are significantly affected by the arrangement of the macromolecules.",
crossref
= "",
}
@InProceedings{ZaunerandConrad96,
author
= "K. P. Zauner and M.
Conrad",
title
= "Simulating the interplay
of structure, kinetics, and dynamics in complex biochemical networks ",
booktitle
= "Proceedings of the German
Conference on Bioinformatics (GCB'96)",
Series
= "Lecture Notes in Computer
Science",
volume
= "1278",
pages
= "336--338",
year = "1996",
editor
= "R. Hofestadt and T.
Lengauer and M. Laffler and D. Schomburg",
publisher
= "Springer Verlag",
address
= "",
url = "",
keywords
= "simulation, implementation,
metabolism, biochemistry, kinetic, structure, spatial, conformation,
CKSD",
abstract = "",
crossref
= "",
}
@InProceedings{Zauner95,
author
= "K. P. Zauner",
title
= "Simulation System for
Studying Spatially Structured Biochemical Interactions",
booktitle
= "Proceedings of BMED'95 and
MEBC'95",
Series
= "",
volume
= "",
pages
= "90--91",
year = "1995",
editor
= "",
publisher
= "",
address
= "",
url = "",
keywords
= "simulation, implementation,
metabolism, biochemistry, kinetic, structure, spatial, conformation,
CKSD",
abstract = "",
crossref
= "",
}
@InProceedings{Zienetal00,
author
= "A. Zien and R. Kuffner and
R. Zimmer and T. Lengauer",
title
= "Analysis of gene
expression data with pathway scores",
booktitle
= "Intelligent Systems for
Molecular Biology",
volume
= "8",
pages
= "407--417",
year = "2000",
editor
= "",
publisher
= "AAAI Press",
address
= "Palo Alto",
url = "ftp://ftp.sdsc.edu/pub/sdsc/biology/ISMB00/151.pdf",
keywords
= "Petri net, reconstruction,
pathway discovery, metabolism",
abstract
= "We present a new approach
for the evaluation of gene expression data. The basic idea is to generate
biologically possible pathways and to score them with respect to gene
expression measurements. We suggest sample scoring functions for different
problem specifications. We assess the significance of the scores for the
investigated pathways by comparison to a number of scores for random pathways.
We show that simple scoring functions can assign statistically significant
scores to biologically relevant pathways. This suggests that the combination of
appropriate scoring functions with the systematic generation of pathways can be
used in order to select the most interesting pathways based on gene expression
measurements.",
crossref
= "PMID:10977101",
}