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De l'analyse de données d'expression à la reconstruction de réseau de gènes

Abstract : The first aspect of this work concerns the pre-processing and analysis of gene expression data in the context of two main projects whose overall aim is to improve the diagnosis and the prognosis of breast cancer and better target treatments. A optimized pre-processing workflow of expression data was established and several analysis have been conducted and have identified genes allowing to point out a characteristic expression profile of nodal status of patients and therapeutic response to a particular chemotherapy, the docetaxel. A new technique for reconstruction of gene networks based on the notion of rules between genes was then proposed, the idea is to offer biologists the possibility to choose among several semantic meanings, the rules they want to generate. The originality of this work is to propose a comprehensive framework that could include a large number of semantic for rules and use identical methods of generation, post-processing and visualization for all proposed semantics. The notion of well-formed semantics i.e. for which Armstrong's axioms are sound and complete, is introduced. A result is also given to know simply whether or not a semantic is well-formed. A visualization of the rules in the form of global networks i.e. including several semantic is proposed. Finally, this approach has been developed as a module called RG integrated into a software dedicated to gene expression data analysis, the TIGR MeV software.
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Contributor : Camille Meyer <>
Submitted on : Thursday, July 12, 2012 - 4:15:41 PM
Last modification on : Friday, October 23, 2020 - 4:49:20 PM
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  • HAL Id : tel-00717382, version 1


Marie Agier. De l'analyse de données d'expression à la reconstruction de réseau de gènes. Bio-informatique [q-bio.QM]. Université Blaise Pascal - Clermont-Ferrand II, 2006. Français. ⟨NNT : 2006CLF21707⟩. ⟨tel-00717382⟩



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