Publications

@conference{Rodríguez-Baena2007,

title = {Discovering alpha–Patterns from Gene Expression Data},

author = {D. Rodríguez-Baena and N. Díaz-Díaz and J. Aguilar-Ruiz and I. A. Nepomuceno-Chamorro},

doi = {10.1007/978-3-540-77226-2_83},

isbn = {978-3-540-77226-2},

year  = {2007},

date = {2007-01-01},

booktitle = {Intelligent Data Engineering and Automated Learning - IDEAL 2007},

pages = {831-839},

abstract = {The biclustering techniques have the purpose of finding subsets of genes that show similar activity patterns under a subset of conditions. In this paper we characterize a specific type of pattern, that we have called ?–pattern, and present an approach that consists in a new biclustering algorithm specifically designed to find ?–patterns, in which the gene expression values evolve across the experimental conditions showing a similar behavior inside a band that ranges from 0 up to a pre–defined threshold called ?. The ? value guarantees the co–expression among genes. We have tested our method on the Yeast dataset and compared the results to the biclustering algorithms of Cheng & Church (2000) and Aguilar & Divina (2005). Results show that the algorithm finds interesting biclusters, grouping genes with similar behaviors and maintaining a very low mean squared residue.},

keywords = {Gene expression analysis},

pubstate = {published},

tppubtype = {conference}

}