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Cited by 350Gene Regulatory Network AnalysisBioinformatics and Genomic NetworksPhilosophy of Biology and Scientific Explanation

The DOI matches its Crossref record; 146 of the 147 references it cites were found in a registry or an index.

Rules for Modeling Signal-Transduction Systems

Hlavacek, William S., Faeder, James R., Blinov, Michael L., Posner, Richard G., Hucka, Michael, Fontana, Walter·2006·Science's STKE
DOI 10.1126/stke.3442006re6
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Abstract

Formalized rules for protein-protein interactions have recently been introduced to represent the binding and enzymatic activities of proteins in cellular signaling. Rules encode an understanding of how a system works in terms of the biomolecules in the system and their possible states and interactions. A set of rules can be as easy to read as a diagrammatic interaction map, but unlike most such maps, rules have precise interpretations. Rules can be processed to automatically generate a mathematical or computational model for a system, which enables explanatory and predictive insights into the system’s behavior. Rules are independent units of a model specification that facilitate model revision. Instead of changing a large number of equations or lines of code, as may be required in the case of a conventional mathematical model, a protein interaction can be introduced or modified simply by adding or changing a single rule that represents the interaction of interest. Rules can be defined and visualized by using graphs, so no specialized training in mathematics or computer science is necessary to create models or to take advantage of the representational precision of rules. Rules can be encoded in a machine-readable format to enable electronic storage and exchange of models, as well as basic knowledge about protein-protein interactions. Here, we review the motivation for rule-based modeling; applications of the approach; and issues that arise in model specification, simulation, and testing. We also discuss rule visualization and exchange and the software available for rule-based modeling.

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Research works printed but not linked: 4

  1. E. O. Voit Computational Analysis of Biochemical Systems (Cambridge Univ. Press Cambridge 2000).
  2. R. J. Bagley J. D. Farmer W. Fontana Evolution of a metabolism. In Artificial Life II C. G. Langton C. Taylor J. D. Farmer S. Rasmussen Eds. (Addison Wesley Redwood City CA 1991) pp. 141–158.
  3. C. Talcott D. L. Dill The pathway logic assistant in Third International Workshop on Computational Methods in Systems Biology G. Plotkin Ed. Edinburgh 3 to 5 April 2005 pp. 228–239.
  4. R. Maimon S. Browning Diagrammatic notation and computational structure of gene networks in Proc. 2nd Int. Conf. Syst. Biol. T.-M. Yi M. Hucka M. Morohashi H. Kitano Eds. (Omnipress Madison WI 2001) pp. 311–317.

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Metadata

Authors
Hlavacek, W. S., Faeder, J. R., Blinov, M. L., Posner, R. G., Hucka, M., & Fontana, W.
Affiliations
  • Los Alamos National Laboratory (US)
  • UConn Health (US)
  • Translational Genomics Research Institute (US)
  • California Institute of Technology (US)
  • Harvard University (US)
ORCID
Venue
Science's STKE
Publisher
American Association for the Advancement of Science (AAAS)
Published
2006-07-18
Volume
2006
Issue
344
Pages
re6-re6
ISSN
1525-8882 (ISSN-L)
DOI
10.1126/stke.3442006re6
OpenAlex
W2069941324
Cited by
350
References
147
Citations by year
2026: 2 · 2025: 2 · 2024: 3 · 2023: 5 · 2022: 10 · 2021: 5 · 2020: 8 · 2019: 14 · 2018: 11 · 2017: 11 · 2016: 15 · 2015: 18 · 2014: 29 · 2013: 36 · 2012: 32
FWCI
2.12
Type
journal article
Language
en
Open access
closed
Locations
  • Science s STKE (publishedVersion)
  • PubMed (publishedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
Funders
National Institute on Aging (R01AG034994)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
Keywords
rule-based models, signal transduction, protein-protein interaction, model specification, model exchange, rule visualization, model simulation, model testing, model revision
MeSH terms
Computer Simulation, Models, Biological, Proteins, Software, Signal Transduction, Protein Interaction Mapping

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