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Méthodes Formelles de la Logique pour la Prédiction de la Structure des Protéines, la Comparaison de Séquences et le Couplage de Modéles.| old_uid | 9212 |
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| title | Méthodes Formelles de la Logique pour la Prédiction de la Structure des Protéines, la Comparaison de Séquences et le Couplage de Modéles. |
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| start_date | 2010/11/04 |
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| schedule | 14h30-15h30 |
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| online | no |
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| summary | Formal methods of Computer Science are more and more applied to the study of biological issues. In literature, they are extensively used to model and simulate
biological systems and to express formal properties of such systems. In the talk I'll show how model checking, game theory, and the combination of temporal logic and parameter learning techniques can be exploited to develop effective solutions to three relevant classes of biological problems: the protein structure prediction and protein folding problems, the sequence comparison problems, and the problems of coupling biological
models and validating the resulting model.
As for the protein structure prediction and protein folding problems, we model the space of protein conformations as a finite transition system whose states are all the possible
conformations of a protein and whose transitions represent admissible transformations of conformations. Then, we show how meaningful properties of such a transition system can be expressed in temporal logic and we use the model checking machinery to lgorithmically check them.
As for the sequence comparison problems, we model biological sequences as labeled structures with a "limited order" relation and we define a criterion which allows one to measure their degree of similarity in terms of the number of remaining rounds
in an Ehrenfeucht-Fraissé game played on such structures.
Finally, as for the last issue is concerned, we study the coupling of different models playing a role in the mammalian cell cycle and in cancer therapies. We show how the
formalization of experimental observations in temporal logic with numerical constraints can be used to automatically validate a coupled model and optimize unknown parameter values with respect to experimental data. We illustrate this constraint-based approach through the coupling of existing biochemical models of the mammalian cell cycle, the circadian clock, the p53/Mdm2 DNA-damage repair system, and irinotecan metabolism. |
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| responsibles | Brière |
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