Finding multiple coherent biclusters in microarray data using variable string length multiobjective genetic algorithm

Authors:
Ujjwal Maulik;Anirban Mukhopadhyay;Sanghamitra Bandyopadhyay
Affiliations:
Department of Computer Science and Engineering, Jadavpur University, Kolkata, India;Department of Computer Science and Engineering, University of Kalyani, Kalyani, India;Indian Statistical Institute, Kolkata, India
Venue:
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
Year:
2009

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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.