Derivation of Qualitative Dynamical Models from Biochemical Networks

Wassim Abou-Jaoudé 1, 2 Jérôme Feret 1 Denis Thieffry 2
1 ANTIQUE - Analyse Statique par Interprétation Abstraite
DI-ENS - Département d'informatique de l'École normale supérieure, Inria Paris-Rocquencourt
Abstract : As technological advances allow a better identification of cellular networks, more and more molecular data are produced allowing the construction of detailed molecular interaction maps. One strategy to get insights into the dynamical properties of such systems is to derive compact dynamical models from these maps, in order to ease the analysis of their dynamics. Starting from a case study, we present a methodology for the derivation of qualitative dynamical models from biochemical networks. Properties are formalised using abstract interpretation. We first abstract states and traces by quotienting the number of instances of chemical species by intervals. Since this abstraction is too coarse to reproduce the properties of interest, we refine it by introducing additional constraints. The resulting abstraction is able to identify the dynamical properties of interest in our case study.
Type de document :
Communication dans un congrès
Olivier Roux; Jérémie Bourdon. CMSB 2015 : Computational Methods in Systems Biology, Sep 2015, Nantes, France. Springer, Lecture Notes in Bioinformatics, 9308, pp.195-207, 2015, Computational Methods in Systems Biology. 〈http://cmsb2015.sciencesconf.org/〉. 〈10.1007/978-3-319-23401-4_17〉
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https://hal.inria.fr/hal-01199243
Contributeur : Jérôme Feret <>
Soumis le : mardi 15 septembre 2015 - 10:37:30
Dernière modification le : jeudi 11 janvier 2018 - 06:25:39

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Wassim Abou-Jaoudé, Jérôme Feret, Denis Thieffry. Derivation of Qualitative Dynamical Models from Biochemical Networks. Olivier Roux; Jérémie Bourdon. CMSB 2015 : Computational Methods in Systems Biology, Sep 2015, Nantes, France. Springer, Lecture Notes in Bioinformatics, 9308, pp.195-207, 2015, Computational Methods in Systems Biology. 〈http://cmsb2015.sciencesconf.org/〉. 〈10.1007/978-3-319-23401-4_17〉. 〈hal-01199243〉

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