An evolutionary approach for biclustering of gene expression data

Authors:
Walaa Sheta;Maha Hany;Shereef Mahdi
Affiliations:
Informatics Institute, Mubarak City for Scientific Research, P.O. Box 21934, New Borgel Arab, Alexandria, Egypt.;Informatics Institute, Mubarak City for Scientific Research, P.O. Box 21934, New Borgel Arab, Alexandria, Egypt.;Information Technology Department, Faculty of Computer and Information, Cairo University, 5 Dr. Ahmed Zewail Street, Orman, Giza, Egypt
Venue:
International Journal of Bio-Inspired Computation
Year:
2010

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Abstract

This paper presents an evolutionary algorithm for analysing the patterns of gene expression on microarray data. Microarray technologies have provided the means to monitor the expression levels of a large number of genes simultaneously. Gene clustering is important in analysing a large body of microarray expression data. The proposed method simultaneously solves gene clustering problems. The proposed algorithm was tested on yeast microarray dataset. The experimental clustering and visual results indicate that the proposed algorithm grouped genes with similar gene expressions. These results indicate that the proposed algorithm has potential in analysing gene expression patterns.