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Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification
Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samp...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583628/ https://www.ncbi.nlm.nih.gov/pubmed/26484222 http://dx.doi.org/10.1016/j.gdata.2015.04.027 |
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author | Ramyachitra, D. Sofia, M. Manikandan, P. |
author_facet | Ramyachitra, D. Sofia, M. Manikandan, P. |
author_sort | Ramyachitra, D. |
collection | PubMed |
description | Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions. |
format | Online Article Text |
id | pubmed-4583628 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-45836282015-10-19 Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification Ramyachitra, D. Sofia, M. Manikandan, P. Genom Data Regular Article Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions. Elsevier 2015-05-23 /pmc/articles/PMC4583628/ /pubmed/26484222 http://dx.doi.org/10.1016/j.gdata.2015.04.027 Text en © 2015 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Regular Article Ramyachitra, D. Sofia, M. Manikandan, P. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification |
title | Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification |
title_full | Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification |
title_fullStr | Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification |
title_full_unstemmed | Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification |
title_short | Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification |
title_sort | interval-value based particle swarm optimization algorithm for cancer-type specific gene selection and sample classification |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583628/ https://www.ncbi.nlm.nih.gov/pubmed/26484222 http://dx.doi.org/10.1016/j.gdata.2015.04.027 |
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