title: A protein structural classes prediction method based on PSI-BLAST profile.
abstract: Knowledge of protein structural classes plays an important role in understanding protein folding patterns. Prediction of protein structural class based solely on sequence data remains to be a challenging problem. In this study, we extract the long-range correlation information and linear correlation information from position-specific score matrix (PSSM). A total of 3600 features are extracted, then, 278 features are selected by a filter feature selection method based on 1189 dataset. To verify the performance of our method (named by LCC-PSSM), jackknife tests are performed on three widely used low similarity benchmark datasets. Comparison of our results with the existing methods shows that our method provides the favorable performance for protein structural class prediction. Stand-alone version of the proposed method (LCC-PSSM) is written in MATLAB language and it can be downloaded from http://bioinfo.zstu.edu.cn/LCC-PSSM/.
authors.affiliation: Department of Sciences, Dalian Nationalities University, Dalian, Liaoning 116600, PR China. Electronic address: sunnyday1979@163.com.
authors.forename: Shuyan
authors.initials: S
authors.lastname: Ding
authors.affiliation: College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, PR China.
authors.forename: Shoujiang
authors.initials: S
authors.lastname: Yan
authors.affiliation: Department of Sciences, Dalian Nationalities University, Dalian, Liaoning 116600, PR China.
authors.forename: Shuhua
authors.initials: S
authors.lastname: Qi
authors.affiliation: College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, PR China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.affiliation: College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, PR China. Electronic address: yaoyuhua2288@163.com.
authors.forename: Yuhua
authors.initials: Y
authors.lastname: Yao
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D056510:Position-Specific Scoring Matrices; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000145:classification*
chemical_list: D011506:Proteins
keywords: Feature selection; Position-specific scoring matrix; Support vector machine