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Gene subset selection for lung cancer classification using a multi-objective strategy

Mohamad, Mohd. Saberi and Omatu, Sigeru and Deris, Safaai and Yoshioka, Michifuci (2008) Gene subset selection for lung cancer classification using a multi-objective strategy. Jurnal Teknologi Maklumat, 20 (3). pp. 133-139. ISSN 0128-3790

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A microarray machine offers the ability to measure the expression levels of thousands of genes simultaneously. It is used to collect the infonnation from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes relative to the small number of available samples, and many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to improved classification accuracy. Hence, this paper proposes a solution to the problems by using a multi-objective strategy in genetic algorithms. This approach is experimented on one gene expression data set, namely the lung cancer. It obtains encouraging result on the data set as compared with an approach that uses single-objective strategy in genetic algorithms.

Item Type:Article
Additional Information:Special issue in computer science
Uncontrolled Keywords:cancer classification, genetic algorithm, gene expression data, gene selection, multi-objective
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions:Computer Science and Information System (Formerly known)
ID Code:11019
Deposited By: Zalinda Shuratman
Deposited On:19 Nov 2010 02:33
Last Modified:01 Nov 2017 04:17

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