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Reseach Article

Data Analysis on DNA Microarray Expression Values using Self Organizing Map

Published on June 2015 by Krishnaveni.s, Lawrance.r
National Conference on Research Issues in Image Analysis and Mining Intelligence
Foundation of Computer Science USA
NCRIIAMI2015 - Number 2
June 2015
Authors: Krishnaveni.s, Lawrance.r
b3b2bfa2-efc2-47ba-a8fe-3a112fdc6ea3

Krishnaveni.s, Lawrance.r . Data Analysis on DNA Microarray Expression Values using Self Organizing Map. National Conference on Research Issues in Image Analysis and Mining Intelligence. NCRIIAMI2015, 2 (June 2015), 6-8.

@article{
author = { Krishnaveni.s, Lawrance.r },
title = { Data Analysis on DNA Microarray Expression Values using Self Organizing Map },
journal = { National Conference on Research Issues in Image Analysis and Mining Intelligence },
issue_date = { June 2015 },
volume = { NCRIIAMI2015 },
number = { 2 },
month = { June },
year = { 2015 },
issn = 0975-8887,
pages = { 6-8 },
numpages = 3,
url = { /proceedings/ncriiami2015/number2/21023-4018/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Research Issues in Image Analysis and Mining Intelligence
%A Krishnaveni.s
%A Lawrance.r
%T Data Analysis on DNA Microarray Expression Values using Self Organizing Map
%J National Conference on Research Issues in Image Analysis and Mining Intelligence
%@ 0975-8887
%V NCRIIAMI2015
%N 2
%P 6-8
%D 2015
%I International Journal of Computer Applications
Abstract

There is a vast need to develop analytical attitude to analyze and to make use of the information contained in gene expression data. A narrative approach for cancer prediction (similarity gene) from DNA microarray data, First apply feature selection using parametric and nonparametric feature selection methods to extract features and select exact feature by combining both methods then apply principal component analysis in microarray data to reduce dimensionality Then the selected principal components are clustered and classified using self organizing map and compare the results.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Clustering Microarray Data Feature Selection Som.