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Research Paper | Computer Science & Engineering | India | Volume 3 Issue 6, June 2014 | Rating: 6.6 / 10
Performance Comparison of Hard and Fuzzy Clustering Algorithms on ESTs of Human Genes
Abhilasha Chaudhuri | Asha Ambhaikar [10]
Abstract: 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