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Methods Mol Biol. 2017;1552:177-184. doi: 10.1007/978-1-4939-6753-7_13.

Finding RNA-Protein Interaction Sites Using HMMs.

Author information

1
Quantitative Biomedical Research Center, Department of Clinical Science, University of Texas Southwestern Medical Center, Dallas, TX, 75290, USA.
2
Department of Mathematics, University of Texas at Arlington, Arlington, TX, 76019, USA.
3
Department of Mathematics, University of Texas at Arlington, Arlington, TX, 76019, USA. Guanghua.Xiao@UTSouthwestern.edu.

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.

KEYWORDS:

Hidden Markov models; Interaction sites; RNA-binding proteins

PMID:
28224499
PMCID:
PMC5568642
DOI:
10.1007/978-1-4939-6753-7_13
[Indexed for MEDLINE]
Free PMC Article

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