A pairwise clustering based biclustering method

Gene expression data is a kind of data matrix used to represent the expression level of different genes under specific conditions simultaneously. Genes which exhibit similar patterns are often functionally related. Microarray data Biclustering is very important for the research on gene regulatory mechanisms. The fact that the elements lying in one bicluster are greatly distributed among the original data matrix adds great difficulty to detect the biclusters. In this paper a novel bicluster detection method is proposed. It makes use of the existing traditional clustering algorithms such as K-means as an intermediate tool to do data clustering. Based on an interesting phenomenon which can be proved to be a characteristic of bicluster, the biclusters are detected one by one. Especially, in order to save the extra clustering processing, a dynamic clustering table´s creation method is applied. At the end of the paper experiment results on the simulated data are presented.