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Communication Dans Un Congrès Année : 2007

GenMiner: mining informative association rules from genomic data

Résumé

GENMINER is a smart adaptation of closed itemsets based association rules extraction to genomic data. It takes advantage of the novel NORDI discretization method and of the JCLOSE algorithm to efficiently generate minimal non-redundant association rules. GENMINER facilitates the integration of numerous sources of biological information such as gene expressions and annotations, and can tacitly integrate qualitative information on biological conditions (age, sex, etc.). We validated this approach analyzing the microarray datasets used by Eisen et al. with several sources of biological annotations. Extracted associations revealed significant co-annotated and co-expressed gene patterns, showing important biological relationships between genes and their features. Several of these relationships are supported by recent biological literature.
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Dates et versions

hal-00361737 , version 1 (25-04-2010)

Identifiants

  • HAL Id : hal-00361737 , version 1

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Ricardo Martinez, Nicolas Pasquier, Claude R. Pasquier. GenMiner: mining informative association rules from genomic data. IEEE BIBM'2007 international conference on Bioinformatics and Biomedecine, Nov 2007, Silicon Valley, United States. pp.15-22. ⟨hal-00361737⟩
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