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

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...

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Main Authors: Mohamad, Mohd. Saberi, Omatu, Sigeru, Deris, Safaai, Yoshioka, Michifuci
Format: Article
Language:English
Published: Penerbit UTM Press 2008
Subjects:
Online Access:http://eprints.utm.my/11019/
http://eprints.utm.my/11019/1/MohdSaberiMohamad2008_GeneSubsetSelectionForLungCancer.pdf
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author Mohamad, Mohd. Saberi
Omatu, Sigeru
Deris, Safaai
Yoshioka, Michifuci
author_facet Mohamad, Mohd. Saberi
Omatu, Sigeru
Deris, Safaai
Yoshioka, Michifuci
author_sort Mohamad, Mohd. Saberi
building UTeM Institutional Repository
collection Online Access
description 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.
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publishDate 2008
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spelling utm-110192017-11-01T04:17:22Z http://eprints.utm.my/11019/ Gene subset selection for lung cancer classification using a multi-objective strategy Mohamad, Mohd. Saberi Omatu, Sigeru Deris, Safaai Yoshioka, Michifuci QA75 Electronic computers. Computer science QA76 Computer software 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. Penerbit UTM Press 2008-12 Article PeerReviewed application/pdf en http://eprints.utm.my/11019/1/MohdSaberiMohamad2008_GeneSubsetSelectionForLungCancer.pdf 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
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Mohamad, Mohd. Saberi
Omatu, Sigeru
Deris, Safaai
Yoshioka, Michifuci
Gene subset selection for lung cancer classification using a multi-objective strategy
title Gene subset selection for lung cancer classification using a multi-objective strategy
title_full Gene subset selection for lung cancer classification using a multi-objective strategy
title_fullStr Gene subset selection for lung cancer classification using a multi-objective strategy
title_full_unstemmed Gene subset selection for lung cancer classification using a multi-objective strategy
title_short Gene subset selection for lung cancer classification using a multi-objective strategy
title_sort gene subset selection for lung cancer classification using a multi-objective strategy
topic QA75 Electronic computers. Computer science
QA76 Computer software
url http://eprints.utm.my/11019/
http://eprints.utm.my/11019/1/MohdSaberiMohamad2008_GeneSubsetSelectionForLungCancer.pdf