Mining maximal local conserved gene clusters from microarray data

Authors:
Yuhai Zhao;Guoren Wang;Ying Yin;Guangyu Xu
Affiliations:
Institute of Computer System, Northeastern University, Shengyang, China;Institute of Computer System, Northeastern University, Shengyang, China;Institute of Computer System, Northeastern University, Shengyang, China;Institute of Computer System, Northeastern University, Shengyang, China
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

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Abstract

In this paper, we explore a novel type of gene cluster called local conserved gene cluster or LC-Cluster for short. A gene’s expression level is local conserved if it is expressed with the similar abundance only on a subset of conditions instead of on all the conditions. A subset of genes which are simultaneously local conserved across the same subset of samples form an LC-Cluster, where the samples correspond to some phenotype and the genes suggest all candidates related to the phenotype. Two efficient algorithms, namely FALCONER and E-FALCONER, are proposed to mine the complete set of maximal LC-Clusters. The test results from both real and synthetic datasets confirm the effectiveness and efficiency of our approaches.