Linking Discrete and Stochastic Models: The Chemical Master Equation as a Bridge between Process Hitting and Proper Generalized Decomposition

  • Courtney Chancellor
  • Amine Ammar
  • Francisco Chinesta
  • Morgan Magnin
  • Olivier Roux
Conference paper

DOI: 10.1007/978-3-642-40708-6_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8130)
Cite this paper as:
Chancellor C., Ammar A., Chinesta F., Magnin M., Roux O. (2013) Linking Discrete and Stochastic Models: The Chemical Master Equation as a Bridge between Process Hitting and Proper Generalized Decomposition. In: Gupta A., Henzinger T.A. (eds) Computational Methods in Systems Biology. CMSB 2013. Lecture Notes in Computer Science, vol 8130. Springer, Berlin, Heidelberg

Abstract

Modeling frameworks bring structure and analysis tools to large and non-intuitive systems but come with certain inherent assumptions and limitations, sometimes to an inhibitive extent. By building bridges in existing models, we can exploit the advantages of each, widening the range of analysis possible for larger, more detailed models of gene regulatory networks. In this paper, we create just such a link between Process Hitting [6,7,8], a recently introduced discrete framework, and the Chemical Master Equation in such a way that allows the application of powerful numerical techniques, namely Proper Generalized Decomposition [1,2,3], to overcome the curse of dimensionality. With these tools in hand, one can exploit the formal analysis of discrete models without sacrificing the ability to obtain a full space state solution, widening the scope of analysis and interpretation possible. As a demonstration of the utility of this methodology, we have applied it here to the p53-mdm2 network [4,5], a widely studied biological regulatory network.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Courtney Chancellor
    • 1
    • 2
  • Amine Ammar
    • 4
  • Francisco Chinesta
    • 2
  • Morgan Magnin
    • 1
    • 3
  • Olivier Roux
    • 1
  1. 1.École Centrale de Nantes, IRCCyN UMR CNRS 6597L’UNAM UniversitéFrance
  2. 2.École Centrale de Nantes, GeM UMR CNRS 6183L’UNAM UniversitéFrance
  3. 3.National Institute of InformaticsTokyoJapan
  4. 4.AngersArts et Metiers ParisTech.France

Personalised recommendations