Biclustering Analysis of Coregulated Biclusters from Gene Expression Data

In this paper, the Biclustering analysis of coregulated biclusters from gene expression data is carried out. Gene expression is the process, which produces functional product from the gene information. Data mining is used to find relevant and useful information from databases. Clustering groups the genes according to the given conditions. Biclustering algorithms belong to a distinct class of clustering algorithms that perform simultaneous clustering of both rows and columns of the gene expression matrix. In this paper a new algorithm, Enhanced Bimax algorithm is proposed. The normalization technique is included which is used to display a coregulated biclusters from gene expression data and grouping the genes in the particular order [1]. In this work, Synthetic Gene Expression dataset is used to display the coregulated genes, developed by Prelic et.al., It contains constant values and coherent values over the conditions and non-overlapping and overlapping clusters. The data matrix contains 10 overlapping cluster and each cluster extends over 5 genes and 15 conditions. KeywordsData mining, biclustering, enhanced bimax algorithm, coregulated biclusters, gene expression data.