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A Survey on Different Feature Selection Methods for Microarray Data Analysis

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 67 - Number 16
Year of Publication: 2013
Authors:
Varuna Tyagi
Anju Mishra
10.5120/11482-7181

Varuna Tyagi and Anju Mishra. Article: A Survey on Different Feature Selection Methods for Microarray Data Analysis. International Journal of Computer Applications 67(16):36-40, April 2013. Full text available. BibTeX

@article{key:article,
	author = {Varuna Tyagi and Anju Mishra},
	title = {Article: A Survey on Different Feature Selection Methods for Microarray Data Analysis},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {67},
	number = {16},
	pages = {36-40},
	month = {April},
	note = {Full text available}
}

Abstract

In the field of medical science diseases diagnosis by Tissue microarrays is one of the active areas of research . There are various gene selection techniques in the literature. Gene selection provides genes subsets that are capable to describe in which category those gene are (active, hyperactive or silent). Various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics are using huge data sets. The problem has been addressed of selection of a small subset of genes from broad patterns of gene expression data, recorded on DNA micro-arrays for cancer classification. Usually till now survey paper discuss various conventional & evolutionary methods of gene selection like filters, wrappers methods.

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