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GenMiner: Mining Informative Association Rules from Genomic Data

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3 Author(s)

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 CLOSE [27] algorithm to efficiently generate min- imal non-redundant association rules. GENMINER facili- tates the integration of numerous sources of biological in- formation such as gene expressions and annotations, and can tacitly integrate qualitative information on biological conditions (age, sex, etc.). We validated this approach ana- lyzing the microarray datasets used by Eisen et al. [10] with several sources of biological annotations. Extracted asso- ciations revealed significant co-annotated and co-expressed gene patterns, showing important biological relationships between genes and their features. Several of these relation- ships are supported by recent biological literature.

Published in:

Bioinformatics and Biomedicine, 2007. BIBM 2007. IEEE International Conference on

Date of Conference:

2-4 Nov. 2007