Refining Dynamics of Gene Regulatory Networks in a Stochastic π-Calculus Framework

  • Loïc Paulevé
  • Morgan Magnin
  • Olivier Roux
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6575)


In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks (GRNs) in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas’ discrete parameters derives from this logical formalism. We offer a compositional approach which comes with a natural translation to the Stochastic π-Calculus. The method we propose consists in successive refinements of generalised dynamics of GRNs. We illustrate the merits and scalability of our framework on the control of the differentiation in a GRN generalising metazoan segmentation processes, and on the analysis of stable states within a large GRN studied in the scope of breast cancer researches.


Stable State Gene Regulatory Network State Graph Process Algebra Stochastic Parameter 
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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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Loïc Paulevé
    • 1
  • Morgan Magnin
    • 1
  • Olivier Roux
    • 1
  1. 1.IRCCyN, UMR CNRS 6597École Centrale de NantesFrance

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