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

Authors:
Seung-Yeon Kim;Jaehyun Sim;Julian Lee
Affiliations:
Computer Aided Molecular Design Research Center, Soongsil University, Seoul, Korea;School of Dentistry, Seoul National University, Seoul, Korea;Department of Bioinformatics and Life Science, Soongsil University, Seoul, Korea
Venue:
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Year:
2006

Citing 3
Cited 1

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Abstract

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.