Goss, P.J. and Peccoud, J.. "Analysis of the stabilizing effect of Rom on the genetic network controlling ColE1 plasmid replication." Pac Symp Biocomput. 1999.
pp. 65-76.
[ .pdf ] [ PubMed ]
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.
Keywords: Cell Division ; Computational Biology_*methods ; *DNA Replication ; Escherichia coli_*genetics ; Escherichia coli_growth and development ; *Models Genetic ; *Plasmids ; Stochastic Processes
Karp, P.D. and Paley, S.M.. "Integrated access to metabolic and genomic data." J Comput Biol. 3
(1).
1996.
pp. 191-212.
[ .pdf ] [ .ps ] [ PubMed ]
The EcoCyc system consists of a knowledge base (KB) that describes the genes and intermediary metabolism of Escherichia coli, and a graphical user interface (GUI) for accessing that knowledge. This paper addresses two problems: How can we create a GUI that provides integrated access to metabolic and genomic data? We describe the design and implementation of visual presentations that closely mimic those found in the biology literature, and that offer hypertext navigation among related entities, and multiple views of the same entity. We employ a frame knowledge representation system (FRS) called HyperTHEO to manage the EcoCyc knowledge base. Among the advantages of FRSs are an expressive data model for capturing the complexities of biological information, and schema-evolution capabilities that facilitate the constant schema changes that biological databases tend to undergo. HyperTHEO also includes rule-based inference facilities that are the foundation of expert systems, a constraint language for maintaining data integrity, and a declarative query language. A graphic KB editor and browser allow the EcoCyc developers to interactively inspect and modify this evolving KB.
Keywords: *Artificial Intelligence ; Computer Communication Networks ; Computer Graphics ; Computers ; *Database Management Systems ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; *Genome ; Bacterial ; Programming Languages ; Systems Integration ; User-Computer Interface
Karp, P.D., Riley, M., Paley, S.M., and Pellegrini-Toole, A.. "EcoCyc: an encyclopedia of Escherichia coli genes and metabolism." Nucleic Acids Res. 24
(1).
1996.
pp. 32-9.
[ .pdf ] [ PubMed ]
The encyclopedia of Escherichia coli genes and metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of E.coli. It describes 2034 genes, 306 enzymes encoded by these genes, 580 metabolic reactions that occur in E.coli and the organization of these reactions into 100 metabolic pathways. The EcoCyc graphical user interface allows query and exploration of the EcoCyc database using visualization tools such as genomic map browsers and automatic layouts of metabolic pathways. EcoCyc spans the space from sequence to function to allow investigation of an unusually broad range of questions. EcoCyc can be thought of as both an electronic review article, because of its copious references to the primary literature, and as an in silico model of E.coli that can be probed and analyzed through computational means.
Keywords: Computer Communication Networks ; *Databases Factual ; Enzymes_metabolism ; Escherichia coli_enzymology ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; *Genome ; Bacterial ; Information Storage and Retrieval ; Software ; User-Computer Interface
Karp, P.D., Riley, M., Paley, S.M., Pellegrini-Toole, A., and Krummenacker, M.. "EcoCyc: Enyclopedia of Escherichia coli Genes and Metabolism." Nucleic Acids Res. 25
(1).
1997.
pp. 43-51.
[ .pdf ] [ PubMed ]
The Encyclopedia of Genes and Metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of Escherichia coli. It describes 2970 genes of E.coli, 547 enzymes encoded by these genes, 702 metabolic reactions that occur in E.coli and the organization of these reactions into 107 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc spans the space from sequence to function to allow scientists to investigate an unusually broad range of questions. EcoCyc can be thought of as both an electronic review article because of its copious references to the primary literature, and as an in silicio model of E.coli metabolism that can be probed and analyzed through computational means.
Keywords: Amino Acid Sequence ; Base Sequence ; *Databases Factual ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; *Genes Bacterial ; User-Computer Interface
Karp, P.D., Riley, M., Paley, S.M., Pellegrini-Toole, A., and Krummenacker, M.. "EcoCyc: Encyclopedia of Escherichia coli genes and metabolism." Nucleic Acids Res. 26
(1).
1998.
pp. 50-3.
[ .pdf ] [ PubMed ]
The encyclopedia of Escherichia coli genes and metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of E.coli. The database describes 3030 genes of E.coli , 695 enzymes encoded by a subset of these genes, 595 metabolic reactions that occur in E.coli, and the organization of these reactions into 123 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc can be thought of as an electronic review article because of its copious references to the primary literature, and as a (qualitative) computational model of E.coli metabolism. EcoCyc is available at URL http://ecocyc.PangeaSystems.com/ecocyc/
Keywords: Computer Graphics ; *Databases Factual_trends ; Encyclopedias ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; *Genes Bacterial ; User-Computer Interface
Karp, P.D., Riley, M., Paley, S.M., Pellegrini-Toole, A., and Krummenacker, M.. "Eco Cyc: encyclopedia of Escherichia coli genes and metabolism." Nucleic Acids Res. 27
(1).
1999.
pp. 55-8.
[ .pdf ] [ PubMed ]
The EcoCyc database describes the genome and gene products of Escherichia coli, its metabolic and signal-transduction pathways, and its tRNAs. The database describes 4391 genes of E.coli, 695 enzymes encoded by a subset of these genes, 904 metabolic reactions that occur in E.coli, and the organization of these reactions into 129 metabolic pathways. The EcoCyc graphical user interface allows scientists to query and explore the EcoCyc database using visualization tools such as genomic-map browsers and automatic layouts of metabolic pathways. EcoCyc has many references to the primary literature, and is a (qualitative) computational model of E. coli metabolism. EcoCyc is available at URL http://ecocyc. PangeaSystems.com/ecocyc/
Keywords: Classification ; *Databases Factual ; Enzymes_genetics ; Enzymes_metabolism ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; *Genes Bacterial ; Genome Bacterial ; Information Storage and Retrieval ; Internet ; Signal Transduction ; User-Computer Interface
Karp, P.D., Riley, M., Saier, M., Paulsen, I.T., Paley, S.M., and Pellegrini-Toole, A.. "The EcoCyc and MetaCyc databases." Nucleic Acids Res. 28
(1).
2000.
pp. 56-9.
[ .pdf ] [ PubMed ]
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/
Keywords: Database Management Systems ; *Databases Factual ; Escherichia coli_genetics ; Genome ; Bacterial
Karp, P.D., Riley, M., Saier, M., Paulsen, I.T., Collado-Vides, J., Paley, S.M., Pellegrini-Toole, A., Bonavides, C., and Gama-Castro, S.. "The EcoCyc Database." Nucleic Acids Res. 30
(1).
2002.
pp. 56-8.
[ .pdf ] [ PubMed ]
EcoCyc is an organism-specific pathway/genome database that describes the metabolic and signal-transduction pathways of Escherichia coli, its enzymes, its transport proteins and its mechanisms of transcriptional control of gene expression. EcoCyc is queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. EcoCyc is available at http://ecocyc.org/.
Keywords: Database Management Systems ; *Databases Genetic ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; Escherichia coli Proteins_*genetics ; Escherichia coli Proteins_*physiology ; Gene Expression Regulation Bacterial ; *Genome Bacterial ; Information Storage and Retrieval ; Internet ; Protein Transport ; Signal Transduction
Karp, P.D.. "Pathway databases: a case study in computational symbolic theories." Science. 293
(5537).
2001.
pp. 2040-4.
[ .pdf ] [ PubMed ]
A pathway database (DB) is a DB that describes biochemical pathways, reactions, and enzymes. The EcoCyc pathway DB (see http://ecocyc.org) describes the metabolic, transport, and genetic-regulatory networks of Escherichia coli. EcoCyc is an example of a computational symbolic theory, which is a DB that structures a scientific theory within a formal ontology so that it is available for computational analysis. It is argued that by encoding scientific theories in symbolic form, we open new realms of analysis and understanding for theories that would otherwise be too large and complex for scientists to reason with effectively.
Keywords: Artificial Intelligence ; *Computational Biology ; Culture Media ; *Databases Factual ; Escherichia coli_enzymology ; Escherichia coli_*genetics ; Escherichia coli_growth and development ; Escherichia coli_*metabolism ; *Genome Bacterial ; Internet ; Software
Stelling, J., Klamt, S., Bettenbrock, K., Schuster, S., and Gilles, E.D.. "Metabolic network structure determines key aspects of functionality and regulation." Nature. 420
(6912).
2002.
pp. 190-3.
[ .pdf ] [ PubMed ]
The relationship between structure, function and regulation in complex cellular networks is a still largely open question. Systems biology aims to explain this relationship by combining experimental and theoretical approaches. Current theories have various strengths and shortcomings in providing an integrated, predictive description of cellular networks. Specifically, dynamic mathematical modelling of large-scale networks meets difficulties because the necessary mechanistic detail and kinetic parameters are rarely available. In contrast, structure-oriented analyses only require network topology, which is well known in many cases. Previous approaches of this type focus on network robustness or metabolic phenotype, but do not give predictions on cellular regulation. Here, we devise a theoretical method for simultaneously predicting key aspects of network functionality, robustness and gene regulation from network structure alone. This is achieved by determining and analysing the non-decomposable pathways able to operate coherently at steady state (elementary flux modes). We use the example of Escherichia coli central metabolism to illustrate the method.
Keywords: Biomass ; Cell Physiology ; Computational Biology ; Computer Simulation ; *Energy Metabolism ; Escherichia coli_genetics ; Escherichia coli_growth and development ; Escherichia coli_*metabolism ; Gene Expression Regulation Bacterial ; *Models Biological ; Phenotype ; Systems Theory
Srivastava, R., Peterson, M.S., and Bentley, W.E.. "Stochastic kinetic analysis of the Escherichia coli stress circuit using sigma(32)-targeted antisense." Biotechnol Bioeng. 75
(1).
2001.
pp. 120-9.
[ PubMed ]
A stochastic Petri net model was developed for simulating the sigma(32) stress circuit in E. coli. Transcription factor sigma(32) is the principal regulator of the response of E. coli to heat shock. Stochastic Petri net (SPN) models are well suited for kinetics characterization of fluxes in biochemical pathways. Notably, there exists a one-to-one mapping of model tokens and places to molecules of particular species. Our model was validated against experiments in which ethanol (inducer of heat shock response) and sigma(32)-targeted antisense (downward regulator) were used to perturb the sigma(32) regulatory pathway. The model was also extended to simulate the effects of recombinant protein production. Results show that the stress response depends heavily on the partitioning of sigma(32) within the cell; that is, sigma(32) becomes immediately available to mediate a stress response because it exists primarily in a sequestered, inactive form, complexed with chaperones DnaK, DnaJ, and GrpE. Recombinant proteins, however, also compete for chaperone proteins, particularly when folded improperly. Our simulations indicate that when the expression of recombinant protein has a low requirement for DnaK, DnaJ, and GrpE, the overall sigma(32) levels may drop, but the level of heat shock proteins will increase. Conversely, when the overexpressed recombinant protein has a strong requirement for the chaperones, a severe response is predicted. Interestingly, both cases were observed experimentally.
Keywords: Antisense Elements (Genetics) ; Computer Simulation ; Escherichia coli_*genetics ; Escherichia coli_*metabolism ; Ethanol ; Gene Expression Regulation Bacterial ; Heat-Shock Proteins_genetics ; Heat-Shock Proteins_metabolism ; *Models Biological ; Recombinant Proteins_genetics ; Sigma Factor_*genetics ; Sigma Factor_*metabolism ; Solvents ; Stochastic Processes