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Cluster utility: a new metric for clustering biological sequences

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2 Author(s)
Lee, J. ; Sch. of Informatics, Indiana Univ., Bloomington, IN, USA ; Sun Kim

We propose cluster utility (CU), a metric that is based on consideration of similarity within a cluster and difference between clusters without metric space assumption. CU showed a very high correlation with the quality index. CU scales very well with data size and its strong correlation with quality index was nearly invariable regardless of data size change. CU can be used in two ways: to guide sequence clustering algorithms and to evaluate clustering results.

Published in:

Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE

Date of Conference:

8-11 Aug. 2005