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.
Supported by National Natural Science Foundation of China under grant 60573089 and 60473074.
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Zhao, Y., Wang, G., Yin, Y., Xu, G. (2006). Mining Maximal Local Conserved Gene Clusters from Microarray Data. In: Li, X., Zaïane, O.R., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2006. Lecture Notes in Computer Science(), vol 4093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811305_39
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DOI: https://doi.org/10.1007/11811305_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37025-3
Online ISBN: 978-3-540-37026-0
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