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Fuzzy biclustering for DNA microarray data analysis

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2 Author(s)
Lixin Han ; Dept. of Comput. Sci. & Eng., Hohai Univ., Nanjing ; Hong Yan

Fuzzy biclustering analysis is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy biclustering clustering method for microarray data analysis. The method employs a combination of the Nelder-Mead and min-max algorithm to construct hierarchically structured biclustering. The method can automatically identify the groups of genes that show similar expression patterns under a specific subset of the samples.

Published in:

Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on

Date of Conference:

1-6 June 2008