Authors : S. Jayalakshmi and S.P. Rajagopalan
Abstract: In a gene expression data matrix a bicluster is a submatrix of genes and conditions that exhibits a high correlation of expression activity across both rows and columns. The problem of locating the most significant bicluster has been shown to be NP-complete. Heuristic approaches such as Cheng and Church�s greedy node deletion algorithm have been previously employed. It is to be expected that stochastic search techniques such as evolutionary algorithms or simulated annealing might improve upon such greedy techniques. In this study we show that an approach based on modified simulated annealing is well suited to this problem and we present a comparative evaluation of simulated annealing and node deletion. We show that modified simulated annealing discovers more significant biclusters.
S. Jayalakshmi and S.P. Rajagopalan , 2007. Application of Modified Simulated Annealing to the Biclustering of Gene Expression Data . International Journal of Soft Computing, 2: 378-381.