Multi-objective optimization using genetic algorithm for gene selection from microarray data

Mohd Saberi Mohamad; Sigeru Omatu; Safaai Deris; Michifumi Yoshioka

doi:10.1109/ICCCE.2008.4580821

Multi-objective optimization using genetic algorithm for gene selection from microarray data

Mohd Saberi Mohamad
, Sigeru Omatu
, Safaai Deris
, Michifumi Yoshioka

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

Microarray technology has been increasingly used in cancer research because of its potential for measuring expression levels of thousands of genes simultaneously in tissue samples. It is used to collect the information from tissue samples regarding gene expression differences that could be useful for cancer classification. However, this classification task faces many challenges due to availability of a smaller number of samples compared to the huge number of genes, 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 an improved accuracy of the classification. Hence, this paper proposes a solution to the problem of gene selection by using a multi-objective approach in genetic algorithm. This approach is experimented on two microarray data sets such as Lung cancer and Mixed-Lineage Leukemia cancer. It obtains encouraging result on those data sets as compared with an approach that uses singleobjective approach.

Original language	English
Title of host publication	Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08
Subtitle of host publication	Global Links for Human Development
Pages	1331-1334
Number of pages	4
DOIs	https://doi.org/10.1109/ICCCE.2008.4580821
Publication status	Published - 2008
Externally published	Yes
Event	International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development - Kuala Lumpur, Malaysia Duration: May 13 2008 → May 15 2008

Publication series

Name	Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development

Other

Other	International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development
Country/Territory	Malaysia
City	Kuala Lumpur
Period	5/13/08 → 5/15/08

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Computer Science Applications
Human-Computer Interaction

Access to Document

10.1109/ICCCE.2008.4580821

Cite this

Mohamad, M. S., Omatu, S., Deris, S., & Yoshioka, M. (2008). Multi-objective optimization using genetic algorithm for gene selection from microarray data. In Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development (pp. 1331-1334). Article 4580821 (Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development). https://doi.org/10.1109/ICCCE.2008.4580821

Multi-objective optimization using genetic algorithm for gene selection from microarray data. / Mohamad, Mohd Saberi; Omatu, Sigeru; Deris, Safaai et al.
Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development. 2008. p. 1331-1334 4580821 (Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mohamad, MS, Omatu, S, Deris, S & Yoshioka, M 2008, Multi-objective optimization using genetic algorithm for gene selection from microarray data. in Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development., 4580821, Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development, pp. 1331-1334, International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development, Kuala Lumpur, Malaysia, 5/13/08. https://doi.org/10.1109/ICCCE.2008.4580821

Mohamad MS, Omatu S, Deris S, Yoshioka M. Multi-objective optimization using genetic algorithm for gene selection from microarray data. In Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development. 2008. p. 1331-1334. 4580821. (Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development). doi: 10.1109/ICCCE.2008.4580821

Mohamad, Mohd Saberi ; Omatu, Sigeru ; Deris, Safaai et al. / Multi-objective optimization using genetic algorithm for gene selection from microarray data. Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development. 2008. pp. 1331-1334 (Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development).

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abstract = "Microarray technology has been increasingly used in cancer research because of its potential for measuring expression levels of thousands of genes simultaneously in tissue samples. It is used to collect the information from tissue samples regarding gene expression differences that could be useful for cancer classification. However, this classification task faces many challenges due to availability of a smaller number of samples compared to the huge number of genes, 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 an improved accuracy of the classification. Hence, this paper proposes a solution to the problem of gene selection by using a multi-objective approach in genetic algorithm. This approach is experimented on two microarray data sets such as Lung cancer and Mixed-Lineage Leukemia cancer. It obtains encouraging result on those data sets as compared with an approach that uses singleobjective approach.",

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Multi-objective optimization using genetic algorithm for gene selection from microarray data

Abstract

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UN SDGs

ASJC Scopus subject areas

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