Parameter inference for asynchronous logical networks using discrete time series
Proceedings of the 9th International Conference on Computational Methods in Systems Biology
Chemical reaction systems, computer algebra and systems biology
CASC'11 Proceedings of the 13th international conference on Computer algebra in scientific computing
Use of timed automata and model-checking to explore scenarios on ecosystem models
Environmental Modelling & Software
Qualitative Reasoning for Biological Network Inference from Systematic Perturbation Experiments
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Time Series Dependent Analysis of Unparametrized Thomas Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Parameter identification and model ranking of thomas networks
CMSB'12 Proceedings of the 10th international conference on Computational Methods in Systems Biology
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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/ Contact: gregory.batt@inria.fr Supplementary information:Supplementary data are available at Bioinformatics online.