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Computational Prediction of RNA-Protein Interactions

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Book cover Promoter Associated RNA

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1543))

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).

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Acknowledgments

This work was supported by NIH grant GM066387 and a Presidential Initiative for Interdisciplinary Research (PIIR) award from Iowa State University to DD. We thank Rasna Walia for valuable discussions and suggestions.

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Correspondence to Drena Dobbs .

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Mann, C.M., Muppirala, U.K., Dobbs, D. (2017). Computational Prediction of RNA-Protein Interactions. In: Napoli, S. (eds) Promoter Associated RNA. Methods in Molecular Biology, vol 1543. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6716-2_8

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  • DOI: https://doi.org/10.1007/978-1-4939-6716-2_8

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  • Publisher Name: Humana Press, New York, NY

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