title: Data of protein-RNA binding sites.
abstract: Despite the increasing number of protein-RNA complexes in structure databases, few data resources have been made available which can be readily used in developing or testing a method for predicting either protein-binding sites in RNA sequences or RNA-binding sites in protein sequences. The problem of predicting protein-binding sites in RNA has received much less attention than the problem of predicting RNA-binding sites in protein. The data presented in this paper are related to the article entitled "PRIdictor: Protein-RNA Interaction predictor" (Tuvshinjargal et al. 2016) [1]. PRIdictor can predict protein-binding sites in RNA as well as RNA-binding sites in protein at the nucleotide- and residue-levels. This paper presents four datasets that were used to test four prediction models of PRIdictor: (1) model RP for predicting protein-binding sites in RNA from protein and RNA sequences, (2) model RaP for predicting protein-binding sites in RNA from RNA sequence alone, (3) model PR for predicting RNA-binding sites in protein from protein and RNA sequences, and (4) model PaR for predicting RNA-binding sites in protein from protein sequence alone. The datasets supplied in this article can be used as a valuable resource to evaluate and compare different methods for predicting protein-RNA binding sites.
authors.affiliation: Department of Computer Science and Engineering, Inha University, Incheon, South Korea.
authors.forename: Wook
authors.initials: W
authors.lastname: Lee
authors.affiliation: Department of Computer Science and Engineering, Inha University, Incheon, South Korea.
authors.forename: Byungkyu
authors.initials: B
authors.lastname: Park
authors.affiliation: Department of Computer Science and Engineering, Inha University, Incheon, South Korea.
authors.forename: Daesik
authors.initials: D
authors.lastname: Choi
authors.affiliation: Department of Computer Science and Engineering, Inha University, Incheon, South Korea.
authors.forename: Kyungsook
authors.initials: K
authors.lastname: Han
keywords: Binding sites; Prediction; Protein-RNA interactions