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28-03-2016 | Original Article | Issue 6/2017

Acta Informatica 6/2017

Precise parameter synthesis for stochastic biochemical systems

Journal:
Acta Informatica > Issue 6/2017
Authors:
Milan Češka, Frits Dannenberg, Nicola Paoletti, Marta Kwiatkowska, Luboš Brim
Important notes
This work has been partially supported by the ERC Advanced Grant VERIWARE, Microsoft Research PhD Scholarship (F. Dannenberg), the Czech Grant Agency grant No. GA15-11089S (L. Brim), and the IT4Innovations Excellence in Science project No. LQ1602 (M. Češka).

Abstract

We consider the problem of synthesising rate parameters for stochastic biochemical networks so that a given time-bounded CSL property is guaranteed to hold, or, in the case of quantitative properties, the probability of satisfying the property is maximised or minimised. Our method is based on extending CSL model checking and standard uniformisation to parametric models, in order to compute safe bounds on the satisfaction probability of the property. We develop synthesis algorithms that yield answers that are precise to within an arbitrarily small tolerance value. The algorithms combine the computation of probability bounds with the refinement and sampling of the parameter space. Our methods are precise and efficient, and improve on existing approximate techniques that employ discretisation and refinement. We evaluate the usefulness of the methods by synthesising rates for three biologically motivated case studies: infection control for a SIR epidemic model; reliability analysis of molecular computation by a DNA walker; and bistability in the gene regulation of the mammalian cell cycle.

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