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2012 23rd International Workshop on Database and Expert Systems Applications (DEXA) (2012)
Sept. 3, 2012 to Sept. 7, 2012
ISSN: 1529-4188
ISBN: 978-1-4673-2621-6
pp: 206-210
Microarrays represent a new technology for measuring expression levels of several genes under various biological conditions generating multiple data. These data can be analyzed by using biclustering method which aims to extract a maximum number of genes and conditions presenting a similar behavior. This paper proposes a new evolutionary approach to obtain maximal high-quality biclusters of highly-correlated genes. The performance of the proposed algorithm is assessed on synthetic gene expression data. Experimental results show that our algorithm competes favorably with several state-of-the-art biclustering algorithms.
biology computing, genetic algorithms, pattern clustering

W. Ayadi, O. Maatouk and H. Bouziri, "Evolutionary Biclustering Algorithm of Gene Expression Data," 2012 23rd International Workshop on Database and Expert Systems Applications(DEXA), Vienna, Austria Austria, 2012, pp. 206-210.
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