title: Predicting lipase types by improved Chou's pseudo-amino acid composition.
abstract: By proposing a improved Chou's 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 > or =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 Chou's 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.
authors.affiliation: Institute of Industrial Biotechnology, Huaqiao University, Quanzhou 362021, Fujian, P R China. zhgyghh@hqu.edu.cn
authors.forename: Guang-Ya
authors.initials: GY
authors.lastname: Zhang
authors.forename: Hong-Chun
authors.initials: HC
authors.lastname: Li
authors.forename: Jia-Qiang
authors.initials: JQ
authors.lastname: Gao
authors.forename: Bai-Shan
authors.initials: BS
authors.lastname: Fang
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000032:analysis*; D019295:Computational Biology; D005240:Feasibility Studies; D008049:Lipase / Q000737:chemistry* / Q000145:classification*; D012680:Sensitivity and Specificity
chemical_list: D000596:Amino Acids; D008049:Lipase