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A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification

The application of microarray data for cancer classification has recently gained in popularity. The main problem that needs to be addressed is the selection of a smaller subset of genes from the thousands of genes in the data that contributes to a disease. This selection process is difficult because...

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Main Authors: Mohamad, Mohd. Saberi, Omatu, Sigeru, Deris, Safaai, Yoshioka, Michifuci, Zainal, Anazida
Format: Article
Language:English
Published: Penerbit UTM Press 2008
Subjects:
QA75 Electronic computers. Computer science
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/8192/1/AnazidaZainal2008_ANewBinaryParticleSwarmOptimizer.pdf
http://eprints.utm.my/id/eprint/8192/
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spelling my.utm.81922017-11-01T04:17:24Z http://eprints.utm.my/id/eprint/8192/ A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification Mohamad, Mohd. Saberi Omatu, Sigeru Deris, Safaai Yoshioka, Michifuci Zainal, Anazida QA75 Electronic computers. Computer science QA Mathematics The application of microarray data for cancer classification has recently gained in popularity. The main problem that needs to be addressed is the selection of a smaller subset of genes from the thousands of genes in the data that contributes to a disease. This selection process is difficult because of the availability of the small number of samples compared to the huge number of genes, many irrelevant genes, and noisy genes. Therefore, this paper proposes an improved binary particle swarm optimization to select a near-optimal (smaller) subset of informative genes that is relevant for cancer classification. Experimental results show that the performance of the proposed method is superior to the experimental method and other related previous works in terms of classification accuracy and the number of selected genes. Penerbit UTM Press 2008 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/8192/1/AnazidaZainal2008_ANewBinaryParticleSwarmOptimizer.pdf Mohamad, Mohd. Saberi and Omatu, Sigeru and Deris, Safaai and Yoshioka, Michifuci and Zainal, Anazida (2008) A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification. Jurnal Teknologi Maklumat, 20 (4). pp. 155-162. ISSN 0128-3790
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
QA Mathematics
spellingShingle QA75 Electronic computers. Computer science
QA Mathematics
Mohamad, Mohd. Saberi
Omatu, Sigeru
Deris, Safaai
Yoshioka, Michifuci
Zainal, Anazida
A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
description The application of microarray data for cancer classification has recently gained in popularity. The main problem that needs to be addressed is the selection of a smaller subset of genes from the thousands of genes in the data that contributes to a disease. This selection process is difficult because of the availability of the small number of samples compared to the huge number of genes, many irrelevant genes, and noisy genes. Therefore, this paper proposes an improved binary particle swarm optimization to select a near-optimal (smaller) subset of informative genes that is relevant for cancer classification. Experimental results show that the performance of the proposed method is superior to the experimental method and other related previous works in terms of classification accuracy and the number of selected genes.
format Article
author Mohamad, Mohd. Saberi
Omatu, Sigeru
Deris, Safaai
Yoshioka, Michifuci
Zainal, Anazida
author_facet Mohamad, Mohd. Saberi
Omatu, Sigeru
Deris, Safaai
Yoshioka, Michifuci
Zainal, Anazida
author_sort Mohamad, Mohd. Saberi
title A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
title_short A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
title_full A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
title_fullStr A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
title_full_unstemmed A new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
title_sort new binary particle swarm optimizer to select a smaller subset of genes for leukaemia cancer classification
publisher Penerbit UTM Press
publishDate 2008
url http://eprints.utm.my/id/eprint/8192/1/AnazidaZainal2008_ANewBinaryParticleSwarmOptimizer.pdf
http://eprints.utm.my/id/eprint/8192/
_version_ 1643644939218714624
score 13.211869

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