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Title: Finding multiple coherent biclusters in microarray data using variable string length multiobjective genetic algorithm. Author: Maulik U, Mukhopadhyay A, Bandyopadhyay S. Journal: IEEE Trans Inf Technol Biomed; 2009 Nov; 13(6):969-75. PubMed ID: 19304489. Abstract: Microarray technology enables the simultaneous monitoring of the expression pattern of a huge number of genes across different experimental conditions. Biclustering in microarray data is an important technique that discovers a group of genes that are coregulated in a subset of conditions. Biclustering algorithms require to identify coherent and nontrivial biclusters, i.e., the biclusters should have low mean squared residue and high row variance. A multiobjective genetic biclustering technique is proposed here that optimizes these objectives simultaneously. A novel encoding scheme that uses variable chromosome length is developed. Moreover, a new quantitative measure to evaluate the goodness of the biclusters is proposed. The performance of the proposed algorithm has been evaluated on both simulated and real-life gene expression datasets, and compared with some other well-known biclustering techniques.[Abstract] [Full Text] [Related] [New Search]