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.
['Ricardo Martinez', 'Claude Pasquier', 'Nicolas Pasquier']
GenMiner: Mining Informative Association Rules from Genomic Data