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Tumor Clustering and Gene Selection Techniques - A Survey

by S. Praba, A. K. Santra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 57 - Number 2
Year of Publication: 2012
Authors: S. Praba, A. K. Santra
10.5120/9083-2570

S. Praba, A. K. Santra . Tumor Clustering and Gene Selection Techniques - A Survey. International Journal of Computer Applications. 57, 2 ( November 2012), 1-8. DOI=10.5120/9083-2570

@article{ 10.5120/9083-2570,
author = { S. Praba, A. K. Santra },
title = { Tumor Clustering and Gene Selection Techniques - A Survey },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 2 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number2/9083-2570/ },
doi = { 10.5120/9083-2570 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:59:22.665427+05:30
%A S. Praba
%A A. K. Santra
%T Tumor Clustering and Gene Selection Techniques - A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 2
%P 1-8
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cancer classification has become one of the active areas of research in the field of medical sciences. Various gene selection and tumor classification techniques have been available in the literature. Gene selection comprises of an exploration for gene subsets that are capable to discriminate tumor tissue from normal tissue. Gene selection is a primary issue in gene expression based tumor classification. Recently, Tissue microarrays have become an extensively used technique to screen for protein expression patterns in a large numbers of tumors. There is increasing interest in transforming the importance of tumor classification from morphologic to molecular. Gene expression profiles provide additional data when compared with morphology and offer a substitute to morphology-based tumor classification systems. So, researchers are very much intentional to develop novel approaches for gene selection and tumor classification. This paper provides a detailed related survey of various gene selection techniques and tumor classification approaches.

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Index Terms

Computer Science
Information Sciences

Keywords

Gene selection Tumor Classification DNA Genetic Algorithm Particle Swarm Intelligence

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