Simulation of large-scale rule-based models

Joshua Colvin, Michael I. Monine, James R. Faeder, William S. Hlavacek, Daniel D. Von Hoff, Richard G Posner

Research output: Contribution to journalArticle

44 Citations (Scopus)

Abstract

Motivation: Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. Results: DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein-protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of StochSim. DYNSTOC differs from StochSim by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions.

Original languageEnglish (US)
Pages (from-to)910-917
Number of pages8
JournalBioinformatics
Volume25
Issue number7
DOIs
StatePublished - 2009

Fingerprint

Proteins
Simulation
Aptitude
Reaction Network
Specifications
Post Translational Protein Processing
Signal transduction
Phosphorylation
Model
Molecular interactions
Binding sites
Signal Transduction
Language
Binding Sites
Chemical reactions
Protein
Availability
Biochemical Networks
Model Specification
Molecules

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability

Cite this

Colvin, J., Monine, M. I., Faeder, J. R., Hlavacek, W. S., Von Hoff, D. D., & Posner, R. G. (2009). Simulation of large-scale rule-based models. Bioinformatics, 25(7), 910-917. https://doi.org/10.1093/bioinformatics/btp066

Simulation of large-scale rule-based models. / Colvin, Joshua; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.; Von Hoff, Daniel D.; Posner, Richard G.

In: Bioinformatics, Vol. 25, No. 7, 2009, p. 910-917.

Research output: Contribution to journalArticle

Colvin, J, Monine, MI, Faeder, JR, Hlavacek, WS, Von Hoff, DD & Posner, RG 2009, 'Simulation of large-scale rule-based models', Bioinformatics, vol. 25, no. 7, pp. 910-917. https://doi.org/10.1093/bioinformatics/btp066
Colvin J, Monine MI, Faeder JR, Hlavacek WS, Von Hoff DD, Posner RG. Simulation of large-scale rule-based models. Bioinformatics. 2009;25(7):910-917. https://doi.org/10.1093/bioinformatics/btp066
Colvin, Joshua ; Monine, Michael I. ; Faeder, James R. ; Hlavacek, William S. ; Von Hoff, Daniel D. ; Posner, Richard G. / Simulation of large-scale rule-based models. In: Bioinformatics. 2009 ; Vol. 25, No. 7. pp. 910-917.
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