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Data Analysis on DNA Microarray Expression Values using Self Organizing Map

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IJCA Proceedings on National Conference on Research Issues in Image Analysis and Mining Intelligence
© 2015 by IJCA Journal
NCRIIAMI 2015 - Number 2
Year of Publication: 2015
Authors:
Krishnaveni. S
Lawrance. R

Krishnaveni.s and Lawrance.r. Article: Data Analysis on DNA Microarray Expression Values using Self Organizing Map. IJCA Proceedings on National Conference on Research Issues in Image Analysis and Mining Intelligence NCRIIAMI 2015(2):6-8, June 2015. Full text available. BibTeX

@article{key:article,
	author = {Krishnaveni.s and Lawrance.r},
	title = {Article: Data Analysis on DNA Microarray Expression Values using Self Organizing Map},
	journal = {IJCA Proceedings on National Conference on Research Issues in Image Analysis and Mining Intelligence},
	year = {2015},
	volume = {NCRIIAMI 2015},
	number = {2},
	pages = {6-8},
	month = {June},
	note = {Full text available}
}

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.

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