K means clustering for gene-gene interaction in episodic memory

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DC Field	Value	Language
dc.contributor.author	Tripathi, S.
dc.contributor.author	Sharma, A.K.
dc.contributor.author	Mishra, R., B.
dc.contributor.author	Pandey, B.
dc.date.accessioned	2020-03-31T08:35:41Z	-
dc.date.available	2020-03-31T08:35:41Z	-
dc.date.issued	2016
dc.identifier.citation	International Journal of Control Theory and Applications, 2016, Vol.9, Specialissue11, pp.5529-5540	en_US
dc.identifier.uri	http://idr.nitk.ac.in/jspui/handle/123456789/11831	-
dc.description.abstract	In this paper K means Clustering Algorithm is used for clustering of candidate genes related to human episodic memory. The clustering of genes is based on gene-gene interaction score. The clusters are supposed to be formed so that distribution of cluster as well as overall interaction Score of clusters should be better. The K-means clustering technique applied to cluster the genes such as in tool STRING 9.1 provides cluster outcome. We compare the results of K means Clustering provided by STRING 9.1 with our K means Clustering Algorithm. The results obtained using K-means shows that clusters formed have better distribution of genes. International Science Press.	en_US
dc.title	K means clustering for gene-gene interaction in episodic memory	en_US
dc.type	Article	en_US
Appears in Collections:	1. Journal Articles

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