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Identification of differentially expressed genes: a comparison between wrapper and filter methods

Vincent Guillemot 1 Vincent Frouin 2 Laurent Le Brusquet 1 Gilles Fleury 1
1 SUPELEC-Campus Gif
2 LEFG - Laboratoire d'Exploration Fonctionnelle des Génomes
Abstract : In order to analyze transcriptomic data along with prior information in a classification context, we are studying the generation of a prediction rule. Transcriptomic data classically present the expression of thousands of genes (variables) with most often only a hundred experiments (individuals). Consequently classical classification methods are not adapted. The solution usually adopted to address this issue is to sort the variables by their relevance, in order to select those which will be used in the classification process.
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Conference papers
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https://hal-supelec.archives-ouvertes.fr/hal-00257928
Contributor : Karine El Rassi <>
Submitted on : Wednesday, February 20, 2008 - 4:25:22 PM
Last modification on : Monday, December 14, 2020 - 12:28:24 PM

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  • HAL Id : hal-00257928, version 1

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CEA | UNIV-PARIS7 | SUPELEC | USPC | UNIV-PARIS

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Vincent Guillemot, Vincent Frouin, Laurent Le Brusquet, Gilles Fleury. Identification of differentially expressed genes: a comparison between wrapper and filter methods. Proceedings of the International Workshop on Machine Learning in Systems Biology, Sep 2007, Evry, France. ⟨hal-00257928⟩

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