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Theses

Inférence de réseaux causaux à partir de données interventionnelles

Abstract : The purpose of this thesis is the use of current transcriptomic data in order to infer a gene regulatory network. These data are often complex, and in particular intervention data may be present. The use of causality theory makes it possible to use these interventions to obtain acyclic causal networks. I question the notion of acyclicity, then based on this theory, I propose several algorithms and / or improvements to current techniques to use this type of data.
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Gilles Monneret. Inférence de réseaux causaux à partir de données interventionnelles. Statistiques [math.ST]. Sorbonne Université, 2018. Français. ⟨NNT : 2018SORUS290⟩. ⟨tel-02379278⟩

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