Abstract
Many biclustering algorithms have been proposed in analyzing the gene expression data and ensemble biclustering methods can improve performance of the biclustering algorithm. We propose a new method of obtaining a variety of constituent biclusters which use different quality measures of bicluster. To demonstrate the efficiency of our methods, experiment on six real gene expression data shows the diversity and biological significance of the biclusters obtained by our methods are higher than that of the compared methods.