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A recursive genetic algorithm to automatically select genes for cancer classification

Deris, Safaai and Mohamad, Mohd. Saberi and Omatu, Sigeru and Yoshiok, Michifumi (2009) A recursive genetic algorithm to automatically select genes for cancer classification. In: Advances in Soft Computing. SpringerLink, pp. 166-174. ISBN 978-354085860-7

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Official URL: http://dx.doi.org/10.1007/978-3-540-85861-4_20

Abstract

Gene expression technology namely microarray, offers the ability to measure the expression levels of thousands of genes simultaneously in a biological organism. Microarray data are expected to be of significant help in the development of efficient cancer diagnosis and classification platform. The main problem that needs to be addressed is the selection of a small subset of genes that contributes to a disease from the thousands of genes measured on microarray that are inherently noisy. Most approaches from previous works have selected the numbers of genes manually and thus, have caused difficulty, especially for beginner biologists. Hence, this paper aims to automatically select a small subset of informative genes that is most relevant for the cancer classification. In order to achieve this aim, a recursive genetic algorithm has been proposed. Experimental results show that the gene subset is small in size and yield better classification accuracy as compared with other previous works as well as four methods experimented in this work. A list of informative genes in the best subsets is also presented for biological usage. © 2009 Springer-Verlag Berlin Heidelberg

Item Type:Book Section
Additional Information:2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008) ISSN : 16153871
Uncontrolled Keywords:cancer classification, gene selection, genetic algorithm, microarray data, recursive genetic algorithm, support vector machine
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Computer Science and Information System (Formerly known)
ID Code:12816
Deposited By: Ms Zalinda Shuratman
Deposited On:30 Jun 2011 05:31
Last Modified:30 Jun 2011 05:31

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