2010/05/12 by Grégory Batt, Michel Le Page, Michel Page +11
Biochemistry, Genetics and Molecular Biology · Computer Science · #Bioinformatics and Genomic Networks #Computational Drug Discovery Methods #FOS: Biological sciences #Gene Regulatory Network Analysis #Quantitative Methods (q-bio.QM) #q-bio.QM
paper · pdf · doi:10.48550/arxiv.1005.2107
arxiv created 2010/05/12 · openalex publication_date 2010/05/12 · arxiv updated 2010/05/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Investigating the relation between the structure and behavior of complex biological networks often involves posing the following two questions: Is a hypothesized structure of a regulatory network consistent with the observed behavior? And can a proposed structure generate a desired behavior? Answering these questions presupposes that we are able to test the compatibility of network structure and behavior. We cast these questions into a parameter search problem for qualitative models of regulatory networks, in particular piecewise-affine differential equation models. 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 experimental data sets. We test the consistency between the IRMA network structure and the time-series data, and search for parameter modifications that would improve the robustness of the external control of the system behavior.