LAPSE:2019.0371
Published Article
LAPSE:2019.0371
Classification of Gene Expression Data Using Multiobjective Differential Evolution
Shijing Ma, Xiangtao Li, Yunhe Wang
February 27, 2019
Gene expression data are usually redundant, and only a subset of them presents distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in bioinformatics. In this paper, a multiobjective binary differential evolution method (MOBDE) is proposed to select a small subset of informative genes relevant to the classification. In the proposed method, firstly, the Fisher-Markov selector is used to choose top features of gene expression data. Secondly, to make differential evolution suitable for the binary problem, a novel binary mutation method is proposed to balance the exploration and exploitation ability. Thirdly, the multiobjective binary differential evolution is proposed by integrating the summation of normalized objectives and diversity selection into the binary differential evolution algorithm. Finally, the MOBDE algorithm is used for feature selection, and support vector machine (SVM) is used as the classifier with the leave-one-out cross-validation method (LOOCV). In order to show the effectiveness and efficiency of the algorithm, the proposed method is tested on ten gene expression datasets. Experimental results demonstrate that the proposed method is very effective.
Keywords
binary differential evolution, binary optimization, differential evolution algorithm, multiobjective method
Suggested Citation
Ma S, Li X, Wang Y. Classification of Gene Expression Data Using Multiobjective Differential Evolution. (2019). LAPSE:2019.0371
Author Affiliations
Ma S: School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
Li X: School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
Wang Y: School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China [ORCID]
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Journal Name
Energies
Volume
9
Issue
12
Article Number
E1061
Year
2016
Publication Date
2016-12-15
Published Version
ISSN
1996-1073
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PII: en9121061, Publication Type: Journal Article
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LAPSE:2019.0371
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doi:10.3390/en9121061
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Feb 27, 2019
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Feb 27, 2019
 
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Calvin Tsay
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