Spatial Information and Boolean Genetic Regulatory Networks.

Abstract : In the course of understanding the functioning of cellular processes, modelling frameworks for biological networks are mandatory in order to reason on the models and their properties. One of the main problems with such modelling frameworks is to determine the dynamics of gene regulatory networks (GRN). Formal techniques, most of them based on model checking, have been applied to select valid dynamics, that is dynamics consistent with biological experiments expressed by temporal properties. The problem is that these formal techniques rapidly become intractable because dynamics associated to the GRN are most of the time very numerous. Recently, it has been observed in in vivo experiments and in genomic and transcriptomic studies, that spatial information are useful to better understand both the mechanisms and the dynamics of GRN. In this paper we propose to extend the modelling framework of R. Thomas in order to introduce such spatial information between genes, and we will show how these further informations allow us to restrict the number of dynamics to consider.
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Sanguthevar Rajasekaran. Bioinformatics and Computational Biology (BICoB), Apr 2008, New Orleans, United States. Springer-Verlag, 5462, pp.270-281, 2009, LNCS. 〈10.1007/978-3-642-00727-9_26 〉
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Matthieu Manceny, Marc Aiguier, Pascale Le Gall, Joan Hérisson, Ivan Junier, et al.. Spatial Information and Boolean Genetic Regulatory Networks.. Sanguthevar Rajasekaran. Bioinformatics and Computational Biology (BICoB), Apr 2008, New Orleans, United States. Springer-Verlag, 5462, pp.270-281, 2009, LNCS. 〈10.1007/978-3-642-00727-9_26 〉. 〈hal-00812184〉

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