An approach to analyzing LOH data of lung cancer based on biclustering and GA

Abstract

There is a close relation between the phenomenon of LOH and malignant tumor. Bicluster algorithms have been applied to the data of loss of heterozygosity analysis and can find the submatrix which is composed by SNPs loci related to cancer. But the conventional Cheng and Church method requires experience values as a threshold, and discovered results must be randomized. In this paper, we use k-means and GA to overcome this shortcoming. The experimental results demonstrate the effectiveness and accuracy of our method in discovering chromosome segments related to suppressor genes of lung cancer. © 2011 Springer-Verlag Berlin Heidelberg.