Predicting Lipase Types by Improved Chous Pseudo-Amino Acid Composition

Title: Predicting Lipase Types by Improved Chous Pseudo-Amino Acid Composition

Volume: 15 Issue: 10

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

Affiliation:

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

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.

Cite this article as:

Zhang Guang-Ya, Li Hong-Chun, Gao Jia-Qiang and Fang Bai-Shan, Predicting Lipase Types by Improved Chous Pseudo-Amino Acid Composition, Protein & Peptide Letters 2008; 15 (10) . https://dx.doi.org/10.2174/092986608786071184

DOI https://dx.doi.org/10.2174/092986608786071184	Print ISSN 0929-8665
Publisher Name Bentham Science Publisher	Online ISSN 1875-5305