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Protein structure abstraction and automatic clustering using secondary structure element sequences

Authors
Park, SHPark, Chang YunKim, DHPark, SHSim, JS
Issue Date
May-2005
Publisher
SPRINGER-VERLAG BERLIN
Citation
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2005, PT 2, v.3481, pp 1284 - 1292
Pages
9
Journal Title
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2005, PT 2
Volume
3481
Start Page
1284
End Page
1292
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/60664
DOI
10.1007/11424826_136
ISSN
0302-9743
1611-3349
Abstract
To study protein clustering is very important in diverse fields such as drug design and environmental industry. For a meaningful clustering, protein structure must be considered. But, protein structures are very complicated and have so much information such as angles, 3-dimensional coordinates. Thus, it is not easy to efficiently compute their relations. In this paper, we present a method to efficiently abstract and cluster protein structures using secondary structure element sequences. Since a secondary structure element sequence is an abstract representation of protein structure, it can be regarded as a useful descriptor to cluster a set of proteins at the abstraction level. Using secondary structure element sequences and their distances, we implemented an automatic protein clustering system and verify their efficiency by experimental results.
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Park, Chang Yun
소프트웨어대학 (소프트웨어학부)
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