Prédiction d'Interactions et Amarrage Protéine-Protéine par combinaison de classifieurs

Jérôme Azé 1, 2
2 AMIB - Algorithms and Models for Integrative Biology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France
Abstract : The work presented in this paper corresponds to eight years of research on the problem of interaction between proteins. I approached the problem of predicting protein-protein interactions in terms of the supervised learning. I am interested in learning predictive models for protein-protein interactions. I studied two different types of interactions: - The protein-protein interaction from the protein interaction network point of view; - Physical interaction between proteins by predicting which residues are actually in interaction (protein-protein docking). The paper is structured as follows: after presenting the problem of supervised learning and unsupervised in the first chapter, the second chapter concern the prediction of protein-protein interaction. The results on the protein-protein docking is presented in the third chapter and finally, perspectives are presented in the last chapter.
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Submitted on : Monday, December 17, 2012 - 4:42:07 PM
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Jérôme Azé. Prédiction d'Interactions et Amarrage Protéine-Protéine par combinaison de classifieurs. Apprentissage [cs.LG]. Université Paris Sud - Paris XI, 2012. ⟨tel-00763947⟩

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