Precise parameter synthesis for stochastic biochemical systems

J 2017

Precise parameter synthesis for stochastic biochemical systems

ČEŠKA, Milan, Frits DANNENBERG, Nicola PAOLETTI, Marta KWIATKOWSKA, Luboš BRIM et. al.

Basic information

Original name

Precise parameter synthesis for stochastic biochemical systems

Authors

ČEŠKA, Milan (203 Czech Republic), Frits DANNENBERG (826 United Kingdom of Great Britain and Northern Ireland), Nicola PAOLETTI (826 United Kingdom of Great Britain and Northern Ireland), Marta KWIATKOWSKA (826 United Kingdom of Great Britain and Northern Ireland) and Luboš BRIM (203 Czech Republic, guarantor, belonging to the institution)

Edition

Acta informatica, Berlin, Springer-Verlag, 2017, 0001-5903

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 0.886

RIV identification code

RIV/00216224:14330/17:00094903

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1007/s00236-016-0265-2

UT WoS

000407713300003

Keywords in English

parameter synthesis; biochemical systems

Abstract

V originále

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.

Links

GA15-11089S, research and development project

Name: Získávání parametrů biologických modelů pomocí techniky ověřování modelů

Investor: Czech Science Foundation

MUNI/A/0897/2016, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VI.

Investor: Masaryk University, Category A

Citovat

ČEŠKA, Milan, Frits DANNENBERG, Nicola PAOLETTI, Marta KWIATKOWSKA and Luboš BRIM. Precise parameter synthesis for stochastic biochemical systems. Acta informatica. Berlin: Springer-Verlag, 2017, vol. 54, No 6, p. 589-623. ISSN 0001-5903. Available from: https://dx.doi.org/10.1007/s00236-016-0265-2.

@article{1388155,
   author = {Češka, Milan and Dannenberg, Frits and Paoletti, Nicola and Kwiatkowska, Marta and Brim, Luboš},
   article_location = {Berlin},
   article_number = {6},
   doi = {http://dx.doi.org/10.1007/s00236-016-0265-2},
   keywords = {parameter synthesis; biochemical systems},
   language = {eng},
   issn = {0001-5903},
   journal = {Acta informatica},
   title = {Precise parameter synthesis for stochastic biochemical systems},
   volume = {54},
   year = {2017}
}

TY  - JOUR
ID  - 1388155
AU  - Češka, Milan - Dannenberg, Frits - Paoletti, Nicola - Kwiatkowska, Marta - Brim, Luboš
PY  - 2017
TI  - Precise parameter synthesis for stochastic biochemical systems
JF  - Acta informatica
VL  - 54
IS  - 6
SP  - 589-623
EP  - 589-623
PB  - Springer-Verlag
SN  - 00015903
KW  - parameter synthesis
KW  - biochemical systems
N2  - 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.
ER  -

ČEŠKA, Milan, Frits DANNENBERG, Nicola PAOLETTI, Marta KWIATKOWSKA and Luboš BRIM. Precise parameter synthesis for stochastic biochemical systems. \textit{Acta informatica}. Berlin: Springer-Verlag, 2017, vol.~54, No~6, p.~589-623. ISSN~0001-5903. Available from: https://dx.doi.org/10.1007/s00236-016-0265-2.

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