DocumentCode
3369730
Title
SEQOPTICS: A Protein Sequence Clustering Method
Author
Chen, Yonghui ; Reilly, Kevin D. ; Sprague, Alan P. ; Guan, Zhijie
Author_Institution
Dept. of Comput. & Inf. Sci., Alabama Univ., Birmingham, AL
Volume
1
fYear
2006
fDate
20-24 June 2006
Firstpage
69
Lastpage
75
Abstract
Protein sequence clustering has been widely used as a part of the analysis of protein structure and function. In most cases single link or graph-based clustering algorithms have been applied. In this paper, we demonstrate an approach of clustering proteins, SEQOPTICS (sequence clustering with OPTICS), which is based on OPTICS (ordering points to identify the clustering structure), an attractive approach due to its emphasis on visualization of results and support for interactive work, e.g., in choosing parameters. OPTICS has not been used, as far as we know, for protein sequence clustering. We have implemented a system with OPTICS at its core to perform protein sequence clustering. In this paper, we test SEQOPTICS with four data sets from different data sources. Visualization of the sequence clustering structure is demonstrated. Our system was evaluated by comparison with other existing methods. Analysis of the results demonstrates that our system perform better by the Jaccard coefficient evaluation criterion
Keywords
biology computing; data visualisation; pattern clustering; proteins; sequences; SEQOPTICS programmed system; data visualization; graph-based clustering algorithm; protein sequence clustering method; protein structure; Biomedical optical imaging; Clustering algorithms; Clustering methods; Data visualization; Databases; Information analysis; Performance analysis; Performance evaluation; Protein sequence; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on
Conference_Location
Hanzhou, Zhejiang
Print_ISBN
0-7695-2581-4
Type
conf
DOI
10.1109/IMSCCS.2006.123
Filename
4673527
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