An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes

Gene expression data could likely be a momentous help in the progress of proficient cancer diagnoses and classification platforms. Lately, many researchers analyze gene expression data using diverse computational intelligence methods, for selecting a small subset of informative genes from the data f...

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Main Authors: Mohd Saberi, Mohamad, Sigeru, Omatu, Safaai, Deris, Yoshioka, Michifumi, Afnizanfaizal, Abdullah, Zuwairie, Ibrahim
Format: Article
Language:English
Published: BioMed Central Ltd. 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/25365/
http://umpir.ump.edu.my/id/eprint/25365/1/An%20enhancement%20of%20binary%20particle%20swarm%20optimization.pdf
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author Mohd Saberi, Mohamad
Sigeru, Omatu
Safaai, Deris
Yoshioka, Michifumi
Afnizanfaizal, Abdullah
Zuwairie, Ibrahim
author_facet Mohd Saberi, Mohamad
Sigeru, Omatu
Safaai, Deris
Yoshioka, Michifumi
Afnizanfaizal, Abdullah
Zuwairie, Ibrahim
author_sort Mohd Saberi, Mohamad
building UMP Institutional Repository
collection Online Access
description Gene expression data could likely be a momentous help in the progress of proficient cancer diagnoses and classification platforms. Lately, many researchers analyze gene expression data using diverse computational intelligence methods, for selecting a small subset of informative genes from the data for cancer classification. Many computational methods face difficulties in selecting small subsets due to the small number of samples compared to the huge number of genes (high-dimension), irrelevant genes, and noisy genes.
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institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T02:38:26Z
publishDate 2013
publisher BioMed Central Ltd.
recordtype eprints
repository_type Digital Repository
spelling ump-253652019-12-10T01:32:39Z http://umpir.ump.edu.my/id/eprint/25365/ An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes Mohd Saberi, Mohamad Sigeru, Omatu Safaai, Deris Yoshioka, Michifumi Afnizanfaizal, Abdullah Zuwairie, Ibrahim TJ Mechanical engineering and machinery Gene expression data could likely be a momentous help in the progress of proficient cancer diagnoses and classification platforms. Lately, many researchers analyze gene expression data using diverse computational intelligence methods, for selecting a small subset of informative genes from the data for cancer classification. Many computational methods face difficulties in selecting small subsets due to the small number of samples compared to the huge number of genes (high-dimension), irrelevant genes, and noisy genes. BioMed Central Ltd. 2013 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25365/1/An%20enhancement%20of%20binary%20particle%20swarm%20optimization.pdf Mohd Saberi, Mohamad and Sigeru, Omatu and Safaai, Deris and Yoshioka, Michifumi and Afnizanfaizal, Abdullah and Zuwairie, Ibrahim (2013) An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes. Algorithms for Molecular Biology, 8 (15). pp. 1-11. ISSN 1748-7188. (Published) https://doi.org/10.1186/1748-7188-8-15 https://doi.org/10.1186/1748-7188-8-15
spellingShingle TJ Mechanical engineering and machinery
Mohd Saberi, Mohamad
Sigeru, Omatu
Safaai, Deris
Yoshioka, Michifumi
Afnizanfaizal, Abdullah
Zuwairie, Ibrahim
An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
title An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
title_full An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
title_fullStr An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
title_full_unstemmed An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
title_short An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
title_sort enhancement of binary particle swarm optimization for gene selection in classifying cancer classes
topic TJ Mechanical engineering and machinery
url http://umpir.ump.edu.my/id/eprint/25365/
http://umpir.ump.edu.my/id/eprint/25365/
http://umpir.ump.edu.my/id/eprint/25365/
http://umpir.ump.edu.my/id/eprint/25365/1/An%20enhancement%20of%20binary%20particle%20swarm%20optimization.pdf