Biclustering Gene Expression Data by an Improved Optimal Algorithm

Ming Qian Wang; Wei Tian; Hao Kang; Wen Ju Gao

doi:10.4028/www.scientific.net/AMM.321-324.2223

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 321-324Biclustering Gene Expression Data by an Improved...

Biclustering Gene Expression Data by an Improved Optimal Algorithm

Abstract:

A novel biclustering algorithm is proposed in this paper, which can be used to cluster gene expression data. One of the contributions of this paper is a novel and effective residue function of the biclustering algorithm. Furthermore, a new optimal algorithm which is mixed by the parallel genetic algorithm and the particle swarm optimal algorithm is firstly used to the algorithm of the biclustering for gene expression data. we compared our algorithm with traditional genetic algorithm in biclustering. The results reveal that novel proposed algorithms could discover the interesting patterns in the gene expression profiles.

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Periodical:

Applied Mechanics and Materials (Volumes 321-324)

Pages:

2223-2226

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.321-324.2223

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Online since:

June 2013

Authors:

Ming Qian Wang, Wei Tian, Hao Kang, Wen Ju Gao

Keywords:

Biclustering, Parallel Immune Genetic Algorithm, Residue Function

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