The recognition of 27-class protein folds: approached by increment of diversity based on multi-characteristic parameters.
Based on the primary sequence, by selecting the pseudo amino acid composition, position weight matrix score, the predicted secondary structure and the second neighbor dipeptide composition as characteristic parameters, an approach of diversity increment for predicting 27-class protein folds is proposed. Overall recognition accuracy reaches 61.10% in the independent testing.
Zhang
Huaiguang
H
College of Sciences, Inner Mongolia University of Technology, Hohhot, 010051, China.
Hu
Xiuzhen
X
Li
Qianzhong
Q
D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D019295:Computational Biology; D030562:Databases, Protein; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein
D000596:Amino Acids; D011506:Proteins