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Authors: Mohd Saberi Mohamad 1 ; Sigeru Omatu 2 ; Michifumi Yoshioka 2 and Safaai Deris 3

Affiliations: 1 Osaka Prefecture University; Universiti Teknologi Malaysia, Malaysia ; 2 Osaka Prefecture University, Japan ; 3 Universiti Teknologi Malaysia, Malaysia

ISBN: 978-989-674-021-4

Keyword(s): Binary particle swarm optimization, Gene selection, Gene expression data, Cancer classification.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Evolutionary Computing ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: In order to select a small subset of informative genes from gene expression data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence methods. However, due to the small number of samples compared to the huge number of genes (high-dimension), irrelevant genes, and noisy genes, many of the computational methods face difficulties to select the small subset. Thus, we propose an enhancement of binary particle swarm optimization to select a small subset of informative genes that is relevant for classifying cancer samples more accurately. In this proposed method, three approaches have been introduced to increase the probability of bits in particle’s positions to be zero. By performing experiments on three different gene expression data sets, we have found that the performance of the proposed method is superior to other previous related works, including the conventional version of binary particle swarm optimization ( BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also produces lower running times compared to BPSO. (More)

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Paper citation in several formats:
Saberi Mohamad M.; Omatu S.; Yoshioka M.; Deris S. and (2010). SELECTING GENES FROM GENE EXPRESSION DATA BY USING AN ENHANCEMENT OF BINARY PARTICLE SWARM OPTIMIZATION FOR CANCER CLASSIFICATION.In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 82-89. DOI: 10.5220/0002732300820089

@conference{icaart10,
author={Mohd {Saberi Mohamad} and Sigeru Omatu and Michifumi Yoshioka and Safaai Deris},
title={SELECTING GENES FROM GENE EXPRESSION DATA BY USING AN ENHANCEMENT OF BINARY PARTICLE SWARM OPTIMIZATION FOR CANCER CLASSIFICATION},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={82-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002732300820089},
isbn={978-989-674-021-4},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - SELECTING GENES FROM GENE EXPRESSION DATA BY USING AN ENHANCEMENT OF BINARY PARTICLE SWARM OPTIMIZATION FOR CANCER CLASSIFICATION
SN - 978-989-674-021-4
AU - Saberi Mohamad, M.
AU - Omatu, S.
AU - Yoshioka, M.
AU - Deris, S.
PY - 2010
SP - 82
EP - 89
DO - 10.5220/0002732300820089

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