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An information-theoretic approach to the prediction of protein structural class

✍ Scribed by Xiaoqi Zheng; Chun Li; Jun Wang

Publisher: John Wiley and Sons
Year: 2009
Tongue: English
Weight: 143 KB
Volume: 31
Category: Article
ISSN: 0192-8651
DOI: 10.1002/jcc.21406

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✦ Synopsis

Abstract

An information‐theoretical approach, which combines a sequence decomposition technique and a fuzzy clustering algorithm, is proposed for prediction of protein structural class. This approach could bypass the process of selecting and comparing sequence features as done previously. First, distances between each pair of protein sequences are estimated using a conditional decomposition technique in information theory. Then, the fuzzy k‐nearest neighbor algorithm is used to identify the structural class of a protein given as set of sample sequences. To verify the strength of our method, we choose three widely used datasets constructed by Chou and Zhou. It is shown by the Jackknife test that our approach represents an improvement in the prediction of accuracy over existing methods. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010

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