TITLE:
A Prediction Method of Protein Disulfide Bond Based on Hybrid Strategy
AUTHORS:
Pengfei Sun, Yunhong Ding, Yuyan Huang, Lei Zhang
KEYWORDS:
Disulfide Bond, Support Vector Machine, Sample Selection
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.9 No.10B,
September
23,
2016
ABSTRACT:
A prediction method of protein disulfide bond based on support vector machine and sample selection is proposed in this paper. First, the protein sequences selected are en-coded according to a certain encoding, input data for the prediction model of protein disulfide bond is generated; Then sample selection technique is used to select a portion of input data as training samples of support vector machine; finally the prediction model training samples trained is used to predict protein disulfide bond. The result of simulation experiment shows that the prediction model based on support vector ma-chine and sample selection can increase the prediction accuracy of protein disulfide bond.