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Analysing biochemical oscillation through probabilistic model checking. (English) Zbl 1283.92023
Cannata, Nicola (ed.) et al., Proceedings of the 2nd workshop – from biology to concurrency and back (FBTC 2008), Reykjavik, Iceland, July 12, 2008. Amsterdam: Elsevier. Electronic Notes in Theoretical Computer Science 229, No. 1, 3-19 (2009).
Summary: 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.
For the entire collection see [Zbl 1278.92003].

MSC:
92C40 Biochemistry, molecular biology
68Q60 Specification and verification (program logics, model checking, etc.)
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