Étude exhaustive de voies de signalisation de grande taille par clustering des trajectoires et caractérisation par analyse sémantique

Jean Coquet 1, 2
Abstract : Signaling pathways describe the extern stimuli responses of a cell. They are indispensable in biological processes such as differentiation, proliferation or apoptosis. The Systems Biology tries to study exhaustively the signalling pathways using static or dynamic models. The number of solutions which explain a biological phenomenon (for example the stimulus reaction of cell) can be very high in large models. First, this thesis proposes some different strategies to group the solutions describing the stimulus signalling with clustering methods and Formal Concept Analysis. Then, it presents the cluster characterization with semantic web methods. Those strategies have been applied to the TGF-beta signaling network, an extracellular stimulus playing an important role in the cancer growing, which helped to identify 5 large groups of trajectories characterized by different biological processes. Next, this thesis confronts the problem of heterogeneous data translation from different bases to a unique formalism. The goal is to be able to generalize the previous study. It proposes a strategy to group signaling pathways of a database to an unique model, then to calculate every signaling trajectory of the stimulus.
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https://tel.archives-ouvertes.fr/tel-01670730
Contributor : Abes Star <>
Submitted on : Wednesday, February 14, 2018 - 10:58:06 AM
Last modification on : Friday, September 13, 2019 - 9:49:21 AM

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Jean Coquet. Étude exhaustive de voies de signalisation de grande taille par clustering des trajectoires et caractérisation par analyse sémantique. Bio-informatique [q-bio.QM]. Université Rennes 1, 2017. Français. ⟨NNT : 2017REN1S073⟩. ⟨tel-01670730v2⟩

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