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Complex Functional Rates in Rule-Based Languages for Biochemistry

  • Cristian Versari
  • Gianluigi Zavattaro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7625)

Abstract

Rule-based languages (like, for example, Kappa, BioNetGen, and BioCham) have emerged as successful models for the representation, analysis, and simulation of bio-chemical systems. In particular Kappa, although based on reactions, differs from traditional chemistry as it allows for a graph-like representation of complexes. It follows the “don’t care, don’t write” approach: a rule contains the description of only those parts of the complexes that are actually involved in a reaction. Hence, given any possible combination of complexes that contain the reactants, such complexes can give rise to the reaction. In this paper we address the problem of extending the “don’t care, don’t write” approach to cases in which the actual structure of the complexes involved in the reaction could affect it (for instance, the mass of the complexes could influence the rate). The solutions that we propose is κ F , an extension of the Kappa-calculus in which rates are defined as functions of the actually involved complexes.

Keywords

Functional Rate Label Transition System Continuous Time Markov Chain Binding Rate System Biology Markup Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cristian Versari
    • 1
  • Gianluigi Zavattaro
    • 2
  1. 1.BioComputing, LIFLUniversity of Lille 1France
  2. 2.Dep. of Computer ScienceUniversity of BolognaItaly

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