Modèles hybrides de réseaux de régulation : étude du couplage des cycles cellulaire et circadien

Abstract : Modelling biological systems has become instrumental to understand complex and emerging phenomena resulting from partially known influences, and to consider controlling an altered system in order to restore a physiological behaviour. Any model, independent of the underlying paradigm, involves parameters governing its dynamics. However, experimental measurements generally do not allow their identification and this remains one of the major problems of modelling. This PhD proposes an automatic method for identifying the dynamic parameters of biological systems in a hybrid modelling framework. The chosen hybrid framework splits the phase space according to the activity of the biological entities, and associates to each of these subspaces a celerity for each of the components. We introduce a continuous time Hoare logic as well as its weakest precondition calculus which, from qualitative and chronometrical experimental observations, constructs the minimum constraints on the model parameters making it compatible with the observations. This calculus leads to a Constraint Satisfaction Problem on real numbers and we show that it can be solved by the AbSolute solver.The Holmes BioNet prototype developed during this PhD can not only automate the parameter identification process from experimental data, but also simulate the evolution of the obtained model in order to compare it with experimental traces. We use this prototype to model the coupling of the cellular and circadian cycles.
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Jonathan Behaegel. Modèles hybrides de réseaux de régulation : étude du couplage des cycles cellulaire et circadien. Bio-informatique [q-bio.QM]. Université Côte d'Azur, 2018. Français. ⟨NNT : 2018AZUR4071⟩. ⟨tel-01962051⟩

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