Performance Comparison of Hard and Fuzzy Clustering Algorithms on ESTs of Human Genes
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Research Paper | Computer Science & Engineering | India | Volume 3 Issue 6, June 2014

Performance Comparison of Hard and Fuzzy Clustering Algorithms on ESTs of Human Genes

Abhilasha Chaudhuri, Asha Ambhaikar

In biological data analysis sequences discovered in laboratory experiments are not properly identified. Biologists attempt to group genes based on the temporal pattern of their expression levels. Clustering algorithms could provide a structure to the data. Hard clustering methods such as K-means or Hierarchical clustering assign each gene to a single cluster; whereas in fuzzy clustering methods a gene possesses varying degrees of membership with more than one cluster. Performances of both type of clustering algorithms are analyzed in this paper.

Keywords: Hard clustering, K-means clustering, Hierarchical clustering, Fuzzy clustering, EST, Fuzzy C-means Clustering

Edition: Volume 3 Issue 6, June 2014

Pages: 1634 - 1638

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How to Cite this Article?

Abhilasha Chaudhuri, Asha Ambhaikar, "Performance Comparison of Hard and Fuzzy Clustering Algorithms on ESTs of Human Genes", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=2014564, Volume 3 Issue 6, June 2014, 1634 - 1638

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