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Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking

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Part of the Lecture Notes in Computer Science book series (LNTCS,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.

This work has been supported by the Czech Science Foundation grant No. GAP202/11/0312. M. Češka has been supported by Ministry of Education, Youth, and Sport project No. CZ.1.07/2.3.00/30.0009 – Employment of Newly Graduated Doctors of Science for Scientific Excellence. D. Šafránek has been supported by EC OP project No. CZ.1.07/2.3.00/20.0256.

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Brim, L., Češka, M., Dražan, S., Šafránek, D. (2013). Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking. In: Sharygina, N., Veith, H. (eds) Computer Aided Verification. CAV 2013. Lecture Notes in Computer Science, vol 8044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39799-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-39799-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39798-1

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