Dataset Information
Efficient parameter search for qualitative models of regulatory networks using symbolic model checking.
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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.Availability
GNA and the IRMA model are available at http://ibis.inrialpes.fr/.
SUBMITTER: Batt G
PROVIDER: S-EPMC2935427 | biostudies-literature | 2010 Sep
REPOSITORIES: biostudies-literature
Publications
Efficient parameter search for qualitative models of regulatory networks using symbolic model checking.
Bioinformatics (Oxford, England) 20100901 18
<h4>Motivation</h4>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.<h4>Results</h4>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 enumer ...[more]