Improving the Biological Relevance of Biclustering for Microarray Data in Using Ensemble Methods

Biclustering is become undoubtedly a current tool for micro array data analysis. Its objective is to identify a set of biclusters, i.e. sub matrices of the original data matrix, presenting a particular pattern. A large number of biclustering methods have already been proposed for gene expression data. Based on ensemble methods, w e propose a new approach improving the performance of all existing biclustering algorithms. Further, we show that the ensemble biclustering can be seen as a problem of binary triclustering and propose an algorithm to solve it. The results on three public micro array datasets show that the ensemble approach produces better biclusters than single approach.