Universiti Teknologi Malaysia Institutional Repository

A model for gene selection and classification of gene expression data

Mohamad, Mohd Saberi and Omatu, Sigeru and Deris, Safaai and Mohd Hashim, Siti Zaiton (2007) A model for gene selection and classification of gene expression data. Artificial Life and Robotics, 11 (2). pp. 219-222. ISSN 1614-7456

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Official URL: http://dx.doi.org/10.1007/s10015-007-0432-1

Abstract

Gene expression data are expected to be of significant help in the development of efficient cancer diagnosis and classification platforms. One problem arising from these data is how to select a small subset of genes from thousands of genes and a few samples that are inherently noisy. This research aims to select a small subset of informative genes from the gene expression data which will maximize the classification accuracy. A model for gene selection and classification has been developed by using a filter approach, and an improved hybrid of the genetic algorithm and a support vector machine classifier. We show that the classification accuracy of the proposed model is useful for the cancer classification of one widely used gene expression benchmark data set

Item Type:Article
Uncontrolled Keywords:Filter approach, gene expression data, gene selection, hybrid approach
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Computer Science and Information System (Formerly known)
ID Code:7392
Deposited By: Nur Amal Zakiah Shamsudin
Deposited On:01 Jan 2009 06:33
Last Modified:01 Jan 2009 06:33

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