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

Grégory Batt 1, * Michel Page 2, 3 Irene Cantone 4 Gregor Goessler 5 Pedro T. Monteiro 2, 6 Hidde de Jong 2
* Corresponding author
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 : Investigating the relation between the structure and behavior of complex biological networks often involves posing the following two questions: Is a hypothesized structure of a regulatory network consistent with the observed behavior? And can a proposed structure generate a desired behavior? Answering these questions presupposes that we are able to test the compatibility of network structure and behavior. We cast these questions into a parameter search problem for qualitative models of regulatory networks, in particular piecewise-affine differential equation models. 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 experimental data sets. We test the consistency between the IRMA network structure and the time-series data, and search for parameter modifications that would improve the robustness of the external control of the system behavior.
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Submitted on : Monday, May 10, 2010 - 5:34:25 PM
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  • HAL Id : inria-00482569, version 1
  • ARXIV : 1005.2107

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Grégory 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. [Research Report] RR-7284, INRIA. 2010. ⟨inria-00482569⟩

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