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Investigating the relation between the structure and behavior of complexbiological networks often involves posing the following two questions: Is ahypothesized structure of a regulatory network consistent with the observedbehavior? And can a proposed structure generate a desired behavior? Answeringthese questions presupposes that we are able to test the compatibility ofnetwork structure and behavior. We cast these questions into a parameter searchproblem for qualitative models of regulatory networks, in particularpiecewise-affine differential equation models. We develop a method based onsymbolic model checking that avoids enumerating all possible parametrizations,and show that this method performs well on real biological problems, using theIRMA synthetic network and benchmark experimental data sets. We test theconsistency between the IRMA network structure and the time-series data, andsearch for parameter modifications that would improve the robustness of theexternal control of the system behavior.

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