title: Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.
abstract: The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.
authors.affiliation: Golden Audit College, Nanjing Audit University, Nanjing 210029, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Ma
authors.affiliation: State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Guo
authors.affiliation: State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Sun
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D057927:Hydrophobic and Hydrophilic Interactions; D015233:Models, Statistical; D012313:RNA / Q000737:chemistry; D016601:RNA-Binding Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D055672:Static Electricity
chemical_list: D000596:Amino Acids; D016601:RNA-Binding Proteins; D012313:RNA