title: Prediction of Protein Structural Class Based on Gapped-Dipeptides and a Recursive Feature Selection Approach.
abstract: The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM) profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE). These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.
authors.affiliation: College of Information Technology, Shanghai Ocean University, Shanghai 201306, China. tgliu@shou.edu.cn.
authors.forename: Taigang
authors.initials: T
authors.lastname: Liu
authors.affiliation: College of Information Technology, Shanghai Ocean University, Shanghai 201306, China. yfqin@shou.edu.cn.
authors.forename: Yufang
authors.initials: Y
authors.lastname: Qin
authors.affiliation: College of Food Science &amp; Technology, Shanghai Ocean University, Shanghai 201306, China. yjwang@shou.edu.cn.
authors.forename: Yongjie
authors.initials: Y
authors.lastname: Wang
authors.affiliation: College of Information Technology, Shanghai Ocean University, Shanghai 201306, China. wchshou@163.com.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Wang
mesh_terms: D004151:Dipeptides / Q000737:chemistry*; D011487:Protein Conformation; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
chemical_list: D004151:Dipeptides
keywords: feature selection; gapped-dipeptide; position-specific score matrix; protein structural class; recursive feature elimination; support vector machine