title: A novel method of predicting protein disordered regions based on sequence features.
abstract: With a large number of disordered proteins and their important functions discovered, it is highly desired to develop effective methods to computationally predict protein disordered regions. In this study, based on Random Forest (RF), Maximum Relevancy Minimum Redundancy (mRMR), and Incremental Feature Selection (IFS), we developed a new method to predict disordered regions in proteins. The mRMR criterion was used to rank the importance of all candidate features. Finally, top 128 features were selected from the ranked feature list to build the optimal model, including 92 Position Specific Scoring Matrix (PSSM) conservation score features and 36 secondary structure features. As a result, Matthews correlation coefficient (MCC) of 0.3895 was achieved on the training set by 10-fold cross-validation. On the basis of predicting results for each query sequence by using the method, we used the scanning and modification strategy to improve the performance. The accuracy (ACC) and MCC were increased by 4% and almost 0.2%, respectively, compared with other three popular predictors: DISOPRED, DISOclust, and OnD-CRF. The selected features may shed some light on the understanding of the formation mechanism of disordered structures, providing guidelines for experimental validation.
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai 200444, China.
authors.forename: Tong-Hui
authors.initials: TH
authors.lastname: Zhao
authors.forename: Min
authors.initials: M
authors.lastname: Jiang
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.forename: Bi-Qing
authors.initials: BQ
authors.lastname: Li
authors.forename: Ning
authors.initials: N
authors.lastname: Zhang
authors.forename: Hai-Peng
authors.initials: HP
authors.lastname: Li
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D056510:Position-Specific Scoring Matrices; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein
chemical_list: D011506:Proteins