Analysing Biochemical Oscillation through Probabilistic Model Checking

  • Authors:

  • Paolo Ballarini;Radu Mardare;Ivan Mura

  • Affiliations:

  • The Microsoft Research -- University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, Povo-Trento 38100, Italy;The Microsoft Research -- University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, Povo-Trento 38100, Italy;The Microsoft Research -- University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, Povo-Trento 38100, Italy

  • Venue:
  • Electronic Notes in Theoretical Computer Science (ENTCS)
  • Year:
  • 2009

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Abstract

Automated verification of stochastic models has been proved to be an effective technique for the analysis of a large class of stochastically behaving systems. In this paper we show how stochastic model-checking can be effectively applied to the analysis of biological systems. We consider a few models of biological systems taken from the literature, and we consider both their encodings as ordinary differential equations and Markovian models. We show that stochastic model-checking verification of biological systems can complement both deterministic and stochastic simulation techniques when dealing with dynamical properties of oscillators. We demonstrate how stochastic model-checking can provide exact quantitative characterization of properties of systems exhibiting oscillatory behavior, providing insights that cannot be obtained with differential equations models and that would require a large number of runs with stochastic simulation approaches.