Predictive analysis for biological regulatory systems – combining discrete and continuous formalisms

Madalena Chaves 1
1 BIOCORE - Biological control of artificial ecosystems
LOV - Laboratoire d'océanographie de Villefranche, CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique
Abstract : The mathematical analysis of models for biological systems covers a wide range of challenging problems that include model assembly or model reduction, parameter estimation, or control of a system towards a desired state. Many different formalisms and methodologies can be used to study these problems, but here the focus will be on Boolean and hybrid modeling frameworks, which facilitate the development of intuitive, computationally amenable, and mathematically rigorous, methods of analysis. The first part of this presentation will address the problem of predicting the dynamical properties of large biological networks, which are often obtained by assembling several smaller modules. Each module will be represented by a Boolean network, the corresponding asynchronous state transition graph and its attractors. Two new objects are introduced, the asymptotic and the cross- graphs, constructed from the strongly connected components of the modules' transition graphs. By using the notion of feedback interconnection, it is shown that the attractors of the large Boolean network can be fully identified in terms of cross-products of the attractors of each module, a method which implies a large computational cost reduction.In the second part some examples will be presented, including a model for cellular growth of bacteria E.coli and a model for gene pattern formation in Drosophila embryo, to illustrate how a combination of different mathematical formalisms leads to gaining quantitative knowledge and predictive power for biological systems.
Type de document :
Communication dans un congrès
Symposium on Mathematical Theory of Networks and Systems (MTNS'14), Jul 2014, Groningen, Netherlands. 〈https://fwn06.housing.rug.nl/mtns2014/〉
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https://hal.inria.fr/hal-01096263
Contributeur : Jean-Luc Gouzé <>
Soumis le : mercredi 17 décembre 2014 - 10:18:02
Dernière modification le : mercredi 21 mars 2018 - 18:57:45

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  • HAL Id : hal-01096263, version 1

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Madalena Chaves. Predictive analysis for biological regulatory systems – combining discrete and continuous formalisms. Symposium on Mathematical Theory of Networks and Systems (MTNS'14), Jul 2014, Groningen, Netherlands. 〈https://fwn06.housing.rug.nl/mtns2014/〉. 〈hal-01096263〉

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