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Oxford University Press (OUP), Bioinformatics, 18(26), p. i603-i610

DOI: 10.1093/bioinformatics/btq387

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

Journal article published in 2010 by Gregory Batt, Michel Page, Irene Cantone, Gregor Goessler, Pedro T. Monteiro ORCID, Hidde de Jong, Hidde Jong
This paper is available in a repository.
This paper is available in a repository.

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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.