title: Computational Prediction of RNA-Protein Interactions.
abstract: Experimental methods for identifying protein(s) bound by a specific promoter-associated RNA (paRNA) of interest can be expensive, difficult, and time-consuming. This chapter describes a general computational framework for identifying potential binding partners in RNA-protein complexes or RNA-protein interaction networks. Protocols for using three web-based tools to predict RNA-protein interaction partners are outlined. Also, tables listing additional webservers and software tools for predicting RNA-protein interactions, as well as databases that contain valuable information about known RNA-protein complexes and recognition sites for RNA-binding proteins, are provided. Although only one of the tools described, lncPro, was designed expressly to identify proteins that bind long noncoding RNAs (including paRNAs), all three approaches can be applied to predict potential binding partners for both coding and noncoding RNAs (ncRNAs).
authors.affiliation: Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, 50011, USA.
authors.forename: Carla M
authors.initials: CM
authors.lastname: Mann
authors.affiliation: Genome Informatics Facility, Iowa State University, Ames, IA, 50011, USA.
authors.forename: Usha K
authors.initials: UK
authors.lastname: Muppirala
authors.affiliation: Genetics, Development and Cell Biology Department, Iowa State University, Ames, IA, 50011, USA. ddobbs@iastate.edu.
authors.forename: Drena
authors.initials: D
authors.lastname: Dobbs
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030541:Databases, Genetic; D011485:Protein Binding; D012313:RNA / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D016601:RNA-Binding Proteins / Q000737:chemistry* / Q000378:metabolism*; D057386:Search Engine; D012984:Software; D060388:Support Vector Machine; D064878:Web Browser
chemical_list: D016601:RNA-Binding Proteins; D012313:RNA
keywords: Computational prediction; Machine learning; RNA-protein databases; RNA-protein interactions; RPISeq; catRAPID; lncPRO; ncRNA