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Protein & Peptide Letters

Editor-in-Chief

ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

Predicting Lipase Types by Improved Chous Pseudo-Amino Acid Composition

Author(s): Guang-Ya Zhang, Hong-Chun Li, Jia-Qiang Gao and Bai-Shan Fang

Volume 15, Issue 10, 2008

Page: [1132 - 1137] Pages: 6

DOI: 10.2174/092986608786071184

Price: $65

Abstract

By proposing a improved Chous pseudo amino acid composition approach to extract the features of the sequences, a powerful predictor based on k-nearest neighbor was introduced to identify the types of lipases according to their sequences. To avoid redundancy and bias, demonstrations were performed on a dataset where none of the proteins has ≥ 25%sequence identity to any other. The overall success rate thus obtained by the 10-fold cross-validation test was over 90%, indicating that the improved Chous pseudo amino acid composition might be a useful tool for extracting the features of protein sequences, or at lease can play a complementary role to many of the other existing approaches.

Keywords: Lipase, improved Chou's pseudo amino acid composition, feature extraction, k-nearest neighbor, bioinformatics


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