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


BACKGROUND
GNA and the IRMA model are available at http://ibis.inrialpes.fr/.
Batt
Gregory
G
INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr
Page
Michel
M
Cantone
Irene
I
Goessler
Gregor
G
Monteiro
Pedro
P
de Jong
Hidde
H
D019985:Benchmarking; D003198:Computer Simulation; D001330:Electronic Data Processing; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D008957:Models, Genetic; D012984:Software; D013561:Symbolism; D049490:Systems Biology; D015003:Yeasts / Q000235:genetics
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