Extraction of Optimal Biclusters from Gene Expression Data

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Abstract

Biclustering is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. In this paper, MAXimal BICluster algorithm (MAXBIC) identifies coherent biclusters of maximum size with high Average Spearman Rho (ASR). This proposed query based algorithm includes three steps viz. three tier pre-processing, identifying a bicluster seed and growing the seed till an optimal bicluster is obtained. Experimental results show the effectiveness of the proposed algorithm. © Springer-Verlag Berlin Heidelberg 2010.

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Bagyamani, J., Thangavel, K., & Rathipriya, R. (2010). Extraction of Optimal Biclusters from Gene Expression Data. In Communications in Computer and Information Science (Vol. 101, pp. 380–383). https://doi.org/10.1007/978-3-642-15766-0_59

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