DocumentCode :
2526923
Title :
Cluster utility: a new metric for clustering biological sequences
Author :
Lee, Jason ; Kim, Sun
Author_Institution :
Sch. of Informatics, Indiana Univ., Bloomington, IN, USA
fYear :
2005
fDate :
8-11 Aug. 2005
Firstpage :
45
Lastpage :
46
Abstract :
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.
Keywords :
biology computing; genetics; graph theory; pattern clustering; statistical analysis; biological sequence clustering; cluster utility; quality index; Bioinformatics; Clustering algorithms; Extraterrestrial measurements; Genomics; Informatics; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE
Print_ISBN :
0-7695-2442-7
Type :
conf
DOI :
10.1109/CSBW.2005.38
Filename :
1540534
Link To Document :
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