title: Prediction of RNA-binding proteins by voting systems.
abstract: It is important to identify which proteins can interact with RNA for the purpose of protein annotation, since interactions between RNA and proteins influence the structure of the ribosome and play important roles in gene expression. This paper tries to identify proteins that can interact with RNA using voting systems. Firstly through Weka, 34 learning algorithms are chosen for investigation. Then simple majority voting system (SMVS) is used for the prediction of RNA-binding proteins, achieving average ACC (overall prediction accuracy) value of 79.72% and MCC (Matthew's correlation coefficient) value of 59.77% for the independent testing dataset. Then mRMR (minimum redundancy maximum relevance) strategy is used, which is transferred into algorithm selection. In addition, the MCC value of each classifier is assigned to be the weight of the classifier's vote. As a result, best average MCC values are attained when 22 algorithms are selected and integrated through weighted votes, which are 64.70% for the independent testing dataset, and ACC value is 82.04% at this moment.
authors.affiliation: School of Materials Science and Engineering, Shanghai University, Shanghai 2000721, China.
authors.forename: C R
authors.initials: CR
authors.lastname: Peng
authors.forename: L
authors.initials: L
authors.lastname: Liu
authors.forename: B
authors.initials: B
authors.lastname: Niu
authors.forename: Y L
authors.initials: YL
authors.lastname: Lv
authors.forename: M J
authors.initials: MJ
authors.lastname: Li
authors.forename: Y L
authors.initials: YL
authors.lastname: Yuan
authors.forename: Y B
authors.initials: YB
authors.lastname: Zhu
authors.forename: W C
authors.initials: WC
authors.lastname: Lu
authors.forename: Y D
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology; D030562:Databases, Protein; D058977:Molecular Sequence Annotation / Q000379:methods*; D012313:RNA / Q000737:chemistry; D016601:RNA-Binding Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D016601:RNA-Binding Proteins; D012313:RNA