Computational Tools for Investigating RNA-Protein Interaction PartnersUsha K Muppirala*, Benjamin A Lewis and Drena Dobbs
Bioinformatics and Computational Biology Program, Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa, USA
- *Corresponding Author:
- Usha K Muppirala
Bioinformatics and Computational Biology Program
Department of Genetics
Development and Cell Biology
Iowa State University
Ames, Iowa, USA
E-mail: [email protected]
Received date: July 22, 2013; Accepted date: August 14, 2013; Published date: August 21, 2013
Citation: Muppirala UK, Lewis BA, Dobbs D (2013) Computational Tools for Investigating RNA-Protein Interaction Partners. J Comput Sci Syst Biol 6:182-187. doi:10.4172/jcsb.1000115
Copyright: © 2013 Muppirala UK, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RNA-protein interactions are important in a wide variety of cellular and developmental processes. Recently, high-throughput experiments have begun to provide valuable information about RNA partners and binding sites for many RNA-binding proteins (RBPs), but these experiments are expensive and time consuming. Thus, computational methods for predicting RNA-Protein interactions (RPIs) can be valuable tools for identifying potential interaction partners of a given protein or RNA, and for identifying likely interfacial residues in RNA-protein complexes. This review focuses on the “partner prediction” problem and summarizes available computational methods, web servers and databases that are devoted to it. New computational tools for addressing the related “interface prediction” problem are also discussed. Together, these computational methods for investigating RNA-protein interactions provide the basis for new strategies for integrating RNA-protein interactions into existing genetic and developmental regulatory networks, an important goal of future research.