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

Abstract : 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.
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Article dans une revue
Bioinformatics, Oxford University Press (OUP), 2008, 24 (22), pp.2643-44
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https://hal.archives-ouvertes.fr/hal-01154857
Contributeur : Claude Pasquier <>
Soumis le : lundi 25 mai 2015 - 08:12:23
Dernière modification le : lundi 4 décembre 2017 - 15:14:13

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  • HAL Id : hal-01154857, version 1

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Ricardo Martinez, Nicolas Pasquier, Claude Pasquier. GenMiner: mining non-redundant association rules from integrated gene expression data and annotations. Bioinformatics, Oxford University Press (OUP), 2008, 24 (22), pp.2643-44. 〈hal-01154857〉

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