Research Article

Rule-based modeling of biochemical networks

  1. James R. Faeder†,
  2. Michael L. Blinov†,
  3. Byron Goldstein,
  4. William S. Hlavacek*

Article first published online: 18 APR 2005

DOI: 10.1002/cplx.20074

Issue

Complexity

Complexity

Special Issue: Understanding Complex Systems: Part II

Volume 10, Issue 4, pages 22–41, March/April 2005

Additional Information

How to Cite

Faeder, J. R., Blinov, M. L., Goldstein, B. and Hlavacek, W. S. (2005), Rule-based modeling of biochemical networks. Complexity, 10: 22–41. doi: 10.1002/cplx.20074

Author Information

  1. Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545

  1. †

    These authors contributed equally to the work

*Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545

Publication History

  1. Issue published online: 18 APR 2005
  2. Article first published online: 18 APR 2005
  3. Manuscript Accepted: 19 DEC 2004
  4. Manuscript Revised: 18 DEC 2004
  5. Manuscript Received: 29 OCT 2004

Funded by

  • National Institutes of Health. Grant Numbers: GM35556, RR18754
  • Department of Energy. Grant Number: W-7405-ENG-36

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Keywords:

  • local rules;
  • automatic model generation;
  • networks;
  • signal transduction;
  • combinatorial complexity;
  • systems biology

Abstract

We present a method for generating a biochemical reaction network from a description of the interactions of components of biomolecules. The interactions are specified in the form of reaction rules, each of which defines a class of reaction associated with a type of interaction. Reactants within a class have shared properties, which are specified in the rule defining the class. A rule also provides a rate law, which governs each reaction in a class, and a template for transforming reactants into products. A set of reaction rules can be applied to a seed set of chemical species and, subsequently, any new species that are found as products of reactions to generate a list of reactions and a list of the chemical species that participate in these reactions, i.e., a reaction network, which can be translated into a mathematical model. © 2005 Wiley Periodicals, Inc. Complexity 10: 22–41, 2005

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