Classification of microarray data using gene networks |
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Authors: | Franck Rapaport Andrei Zinovyev Marie Dutreix Emmanuel Barillot Jean-Philippe Vert |
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Affiliation: | 1.lnstitut Curie,Service de Bioinformatique,Paris,France;2.Ecole des Mines de Paris,Centre for Computational Biology,Fontainebleau,France;3.lnstitut Curie, CNRS-UMR 2027, Batiment 110,Centre Universitaire,Orsay,France |
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Abstract: | Background Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation. |
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