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Finding RNA–Protein Interaction Sites Using HMMs

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Book cover Hidden Markov Models

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1552))

Abstract

RNA-binding proteins play important roles in the various stages of RNA maturation through binding to its target RNAs. Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Several Hidden Markov model-based (HMM) approaches have been suggested to identify protein–RNA binding sites from CLIP-Seq datasets. In this chapter, we describe how HMM can be applied to analyze CLIP-Seq datasets, including the bioinformatics preprocessing steps to extract count information from the sequencing data before HMM and the downstream analysis steps following peak-calling.

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Correspondence to Guanghua Xiao .

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Wang, T., Yun, J., Xie, Y., Xiao, G. (2017). Finding RNA–Protein Interaction Sites Using HMMs. In: Westhead, D., Vijayabaskar, M. (eds) Hidden Markov Models. Methods in Molecular Biology, vol 1552. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6753-7_13

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  • DOI: https://doi.org/10.1007/978-1-4939-6753-7_13

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6751-3

  • Online ISBN: 978-1-4939-6753-7

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