Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking

  • Luboš Brim
  • Milan Češka
  • Sven Dražan
  • David Šafránek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8044)

Abstract

We propose an automated method for exploring kinetic parameters of stochastic biochemical systems. The main question addressed is how the validity of an a priori given hypothesis expressed as a temporal logic property depends on kinetic parameters. Our aim is to compute a landscape function that, for each parameter point from the inspected parameter space, returns the quantitative model checking result for the respective continuous time Markov chain. Since the parameter space is in principle dense, it is infeasible to compute the landscape function directly. Hence, we design an effective method that iteratively approximates the lower and upper bounds of the landscape function with respect to a given accuracy. To this end, we modify the standard uniformization technique and introduce an iterative parameter space decomposition. We also demonstrate our approach on two biologically motivated case studies.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Luboš Brim
    • 1
  • Milan Češka
    • 1
  • Sven Dražan
    • 1
  • David Šafránek
    • 1
  1. 1.Systems Biology Laboratory at Faculty of InformaticsMasaryk UniversityBrnoCzech Republic

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