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An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes

Mohamad, Mohd. Saberi and Omatu, Sigeru and Deris, Safaai and Yoshioka, Michifumi (2013) An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes. Algorithms For Molecular Biology, 8 . ISSN 1748-7188


Official URL: http://dx.doi.org/10.1186/1748-7188-8-15


Background: Gene expression data could likely be a momentous help in the progress of proficient cancer diagnoses and classification platforms. Lately, many researchers analyze gene expression data using diverse computational intelligence methods, for selecting a small subset of informative genes from the data for cancer classification. Many computational methods face difficulties in selecting small subsets due to the small number of samples compared to the huge number of genes (high-dimension), irrelevant genes, and noisy genes.Methods: We propose an enhanced binary particle swarm optimization to perform the selection of small subsets of informative genes which is significant for cancer classification. Particle speed, rule, and modified sigmoid function are introduced in this proposed method to increase the probability of the bits in a particle's position to be zero. The method was empirically applied to a suite of ten well-known benchmark gene expression data sets.Results: The performance of the proposed method proved to be superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also requires lower computational time compared to BPSO

Item Type:Article
Uncontrolled Keywords:binary particle swarm optimization, gene selection, gene expression data, optimization
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:49116
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:02 Dec 2015 10:09
Last Modified:14 Oct 2018 16:21

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