Fuzzy k-nearest neighbor method for protein secondary structure prediction and its parallel implementation

被引:0
|
作者
Kim, Seung-Yeon [1 ]
Sim, Jaehyun
Lee, Julian
机构
[1] Soongsil Univ, Comp Aided Mol Design Res Ctr, Seoul 156743, South Korea
[2] Seoul Natl Univ, Sch Dent, Seoul 110749, South Korea
[3] Soongsil Univ, Dept Bioinformat & Life Sci, Seoul 156743, South Korea
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中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Fuzzy k-nearest neighbor method is a generalization of nearest neighbor method, the simplest algorithm for pattern classification. One of the important areas for application of the pattern classification is the protein secondary structure prediction, an important topic in the field of bioinformatics. In this work, we develop a parallel algorithm for protein secondary structure prediction, based on the fuzzy k-nearest neighbor method, that uses evolutionary profile obtained from PSI-BLAST (Position Specific Iterative Basic Local Sequence Alignment Tool) as the feature vectors.
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收藏
页码:444 / 453
页数:10
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