@inbook{5491e8eede6642ffac8a4d4333e9ff2f,
title = "Finding RNA–Protein interaction sites using HMMs",
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",
author = "Tao Wang and Jonghyun Yun and Yang Xie and Guanghua Xiao",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media LLC 2017.",
year = "2017",
doi = "10.1007/978-1-4939-6753-7_13",
language = "English (US)",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "177--184",
booktitle = "Methods in Molecular Biology",
}