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DC Field | Value | Language |
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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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