Multiobjective fuzzy biclustering in microarray data: Method and a new performance measure

Author

Maulik, Ujjwal ; Mukhopadhyay, Anirban ; Bandyopadhyay, Sanghamitra ; Zhang, Michael Q. ; Zhang, Xuegong

Author_Institution

Dept. of Comput. Sci. & Eng., Jadavpur Univ., Kolkata

fYear

2008

fDate

1-6 June 2008

Firstpage

1536

Lastpage

1543

Abstract

Objective of any biclustering algorithm in microarray data is to discover a subset of genes that are expressed similarly in a subset of conditions. The boundaries of biclusters usually overlap as genes and conditions may belong to different biclusters with different membership degrees. Hence the notion of fuzzy sets is useful for discovering such overlapping biclusters. In this article an attempt has been made to develop a multiobjective genetic algorithm based approach for probabilistic fuzzy biclustering that minimizes the residual and maximizes cluster size and expression profile variance. A novel variable string length encoding has been proposed in this regard that encodes multiple biclusters in a single string. Also a new performance measure that reflects how a bicluster is statistically distinguished from the background is proposed. Performance of the proposed algorithm has been compared with some well known biclustering algorithms.

Keywords

fuzzy set theory; genetic algorithms; pattern clustering; expression profile variance; fuzzy sets; microarray data; multiobjective fuzzy biclustering; multiobjective genetic algorithm; performance measures; variable string length encoding; Clustering algorithms; Clustering methods; Computer science; Data mining; Databases; Encoding; Fuzzy sets; Genetic algorithms; Q measurement; Space technology; Fuzzy biclustering; expression profile variance; fuzzy K-medoids; mean squared residue; multiobjective genetic algorithm; statistical difference from background; variable string length;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-1822-0

Electronic_ISBN

978-1-4244-1823-7

Type

conf

DOI

10.1109/CEC.2008.4630996

Filename

4630996