Probabilistic Model Checking of Complex Biological Pathways

  • J. Heath
  • M. Kwiatkowska
  • G. Norman
  • D. Parker
  • O. Tymchyshyn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4210)


Probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including security and communication protocols, distributed algorithms and power management. In this paper we illustrate its applicability to a complex biological system: the FGF (Fibroblast Growth Factor) signalling pathway. We give a detailed description of how this case study can be modelled in the probabilistic model checker PRISM, discussing some of the issues that arise in doing so, and show how we can thus examine a rich selection of quantitative properties of this model. We present experimental results for the case study under several different scenarios and provide a detailed analysis, illustrating how this approach can be used to yield a better understanding of the dynamics of the pathway.


Fibroblast Growth Factor Model Check Fibroblast Growth Factor Receptor Continuous Time Markov Chain Probabilistic Model Check 
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 2006

Authors and Affiliations

  • J. Heath
    • 1
  • M. Kwiatkowska
    • 2
  • G. Norman
    • 2
  • D. Parker
    • 2
  • O. Tymchyshyn
    • 2
  1. 1.School of Biosciences 
  2. 2.School of Computer ScienceUniversity of BirminghamBirminghamUK

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