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Finding Multiple Coherent Biclusters in Microarray Data Using Variable String Length Multiobjective Genetic Algorithm

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3 Author(s)
Ujjwal Maulik ; Dept. of Comput. Sci. & Eng., Jadavpur Univ., Kolkata, India ; Anirban Mukhopadhyay ; Sanghamitra Bandyopadhyay

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.

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IEEE Transactions on Information Technology in Biomedicine  (Volume:13 ,  Issue: 6 )