Efficient parameter search for qualitative models of regulatory networks using symbolic model checking

Gregory Batt 1 Michel Page 2, 3 Irene Cantone 4 Gregor Goessler 5 Pedro T. Monteiro 2, 6 Hidde Jong 2, *
* Auteur correspondant
1 CONTRAINTES - Constraint programming
Inria Paris-Rocquencourt
2 IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks
LAPM - Laboratoire Adaptation et pathogénie des micro-organismes [Grenoble], Inria Grenoble - Rhône-Alpes, Institut Jean Roget
5 POP ART - Programming languages, Operating Systems, Parallelism, and Aspects for Real-Time
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Motivation: Investigating the relation between the structure and behavior of complex biological networks often involves posing the question if the hypothesized structure of a regulatory network is consistent with the observed behavior, or if a proposed structure can generate a desired behavior. Results: The above questions can be cast into a parameter search problem for qualitative models of regulatory networks. We develop a method based on symbolic model checking that avoids enumerating all possible parametrizations, and show that this method performs well on real biological problems, using the IRMA synthetic network and benchmark datasets. We test the consistency between IRMA and time-series expression profiles, and search for parameter modifications that would make the external control of the system behavior more robust.
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Contributeur : Gaëlle Rivérieux <>
Soumis le : jeudi 21 février 2013 - 14:33:00
Dernière modification le : vendredi 25 mai 2018 - 12:02:03

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Gregory Batt, Michel Page, Irene Cantone, Gregor Goessler, Pedro T. Monteiro, et al.. Efficient parameter search for qualitative models of regulatory networks using symbolic model checking. Bioinformatics, Oxford University Press (OUP), 2010, 26, pp.i603-i610. 〈10.1093/bioinformatics/btq387〉. 〈hal-00793024〉



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