title: RISP: a web-based server for prediction of RNA-binding sites in proteins.
abstract: Protein-RNA interactions play significant roles in a number of biological activities, such as protein synthesis, regulation of gene expression. Here we propose a hybrid RISP (RNA-interaction site prediction) method, using support vector machine (SVM) in conjunction with evolutionary information of amino acid sequences in terms of their position-specific scoring matrices (PSSMs) for prediction of RNA-binding sites. The results show that our RISP method has 72.2% net prediction (NP) (61.0% sensitivity and 83.3% specificity). When compared with previous studies, this novel method appears more accurate and better generalization abilities. RISP is freely available at http://grc.seu.edu.cn/RISP. Given a protein sequence, RISP decides whether residue in the protein is RNA-binding or not (optimal prediction), and gives the confidence value, 'high specificity' prediction and 'high sensitivity' prediction.
authors.affiliation: Department of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China. zhlu@seu.edu.cn
authors.forename: Jing
authors.initials: J
authors.lastname: Tong
authors.forename: Peng
authors.initials: P
authors.lastname: Jiang
authors.forename: Zu-Hong
authors.initials: ZH
authors.lastname: Lu
mesh_terms: D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D001665:Binding Sites; D030562:Databases, Protein; D020407:Internet; D011506:Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D012313:RNA / Q000378:metabolism*
chemical_list: D011506:Proteins; D012313:RNA