An improved binary particle swarm optimisation for gene selection in classifying cancer classes

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

doi:10.1007/978-3-642-02481-8_72

An improved binary particle swarm optimisation for gene selection in classifying cancer classes

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

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

3 Citations (Scopus)

Abstract

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 optimisation 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 a standard version of particle swarm optimisation and other related previous works in terms of classification accuracy and the number of selected genes.

Original language	English
Title of host publication	Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings
Pages	495-502
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-02481-8_72
Publication status	Published - 2009
Externally published	Yes
Event	10th International Work-Conference on Artificial Neural Networks, IWANN 2009 - Salamanca, Spain Duration: Jun 10 2009 → Jun 12 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5518 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Work-Conference on Artificial Neural Networks, IWANN 2009
Country/Territory	Spain
City	Salamanca
Period	6/10/09 → 6/12/09

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Gene selection
Hybrid approach
Microarray data
Particle swarm optimisation

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-02481-8_72

Cite this

Mohamad, M. S., Omatu, S., Deris, S., Yoshioka, M., & Zainal, A. (2009). An improved binary particle swarm optimisation for gene selection in classifying cancer classes. In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings (PART 2 ed., pp. 495-502). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5518 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-02481-8_72

An improved binary particle swarm optimisation for gene selection in classifying cancer classes. / Mohamad, Mohd Saberi; Omatu, Sigeru; Deris, Safaai et al.
Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2. ed. 2009. p. 495-502 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5518 LNCS, No. PART 2).

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

Mohamad, MS, Omatu, S, Deris, S, Yoshioka, M & Zainal, A 2009, An improved binary particle swarm optimisation for gene selection in classifying cancer classes. in Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5518 LNCS, pp. 495-502, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, 6/10/09. https://doi.org/10.1007/978-3-642-02481-8_72

Mohamad MS, Omatu S, Deris S, Yoshioka M, Zainal A. An improved binary particle swarm optimisation for gene selection in classifying cancer classes. In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2 ed. 2009. p. 495-502. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-02481-8_72

Mohamad, Mohd Saberi ; Omatu, Sigeru ; Deris, Safaai et al. / An improved binary particle swarm optimisation for gene selection in classifying cancer classes. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2. ed. 2009. pp. 495-502 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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An improved binary particle swarm optimisation for gene selection in classifying cancer classes

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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