Rule‐based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

  • Lily A. Chylek
    Department of Chemistry and Chemical Biology Cornell University Ithaca NY USA
  • Leonard A. Harris
    Department of Computational and Systems Biology University of Pittsburgh School of Medicine Pittsburgh PA USA
  • Chang‐Shung Tung
    Theoretical Biology and Biophysics Group Theoretical Division, Los Alamos National Laboratory Los Alamos NM USA
  • James R. Faeder
    Department of Computational and Systems Biology University of Pittsburgh School of Medicine Pittsburgh PA USA
  • Carlos F. Lopez
    Department of Cancer Biology and Center for Quantitative Sciences Vanderbilt University School of Medicine Nashville TN USA
  • William S. Hlavacek
    Theoretical Division and Center for Nonlinear Studies Los Alamos National Laboratory Los Alamos NM USA

説明

<jats:p>Rule‐based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model‐specification languages, and recently developed tools designed for specification of rule‐based models allow one to leverage powerful software engineering capabilities. A rule‐based model comprises a set of rules, which can be processed by general‐purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). <jats:italic>WIREs Syst Biol Med</jats:italic> 2014, 6:13–36. doi: 10.1002/wsbm.1245</jats:p><jats:p>This article is categorized under: <jats:list list-type="explicit-label"> <jats:list-item><jats:p>Biological Mechanisms > Cell Signaling</jats:p></jats:list-item> <jats:list-item><jats:p>Analytical and Computational Methods > Computational Methods</jats:p></jats:list-item> <jats:list-item><jats:p>Models of Systems Properties and Processes > Mechanistic Models</jats:p></jats:list-item> </jats:list></jats:p>

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