Literature DB >> 18799482

GenMiner: mining non-redundant association rules from integrated gene expression data and annotations.

Ricardo Martinez1, Nicolas Pasquier, Claude Pasquier.   

Abstract

UNLABELLED: GenMiner is an implementation of association rule discovery dedicated to the analysis of genomic data. It allows the analysis of datasets integrating multiple sources of biological data represented as both discrete values, such as gene annotations, and continuous values, such as gene expression measures. GenMiner implements the new NorDi (normal discretization) algorithm for normalizing and discretizing continuous values and takes advantage of the Close algorithm to efficiently generate minimal non-redundant association rules. Experiments show that execution time and memory usage of GenMiner are significantly smaller than those of the standard Apriori-based approach, as well as the number of extracted association rules. AVAILABILITY: The GenMiner software and supplementary materials are available at http://bioinfo.unice.fr/publications/genminer_article/ and http://keia.i3s.unice.fr/?Implementations:GenMiner SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mesh:

Year:  2008        PMID: 18799482     DOI: 10.1093/bioinformatics/btn490

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


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