Multi-scale chromatin state annotation using a hierarchical hidden Markov model

The impact of chromatin structure on gene expression makes it integral to our understanding of developmental and disease processes. Here, the authors introduce a hierarchical hidden Markov model to systematically annotate chromatin states at multiple length scales, and demonstrate its utility for th...

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Autores principales:	Eugenio Marco, Wouter Meuleman, Jialiang Huang, Kimberly Glass, Luca Pinello, Jianrong Wang, Manolis Kellis, Guo-Cheng Yuan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/2004377ed7d24b28b5e7aa6b466a4072
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id	oai:doaj.org-article:2004377ed7d24b28b5e7aa6b466a4072
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spelling	oai:doaj.org-article:2004377ed7d24b28b5e7aa6b466a40722021-12-02T15:38:57ZMulti-scale chromatin state annotation using a hierarchical hidden Markov model10.1038/ncomms150112041-1723https://doaj.org/article/2004377ed7d24b28b5e7aa6b466a40722017-04-01T00:00:00Zhttps://doi.org/10.1038/ncomms15011https://doaj.org/toc/2041-1723The impact of chromatin structure on gene expression makes it integral to our understanding of developmental and disease processes. Here, the authors introduce a hierarchical hidden Markov model to systematically annotate chromatin states at multiple length scales, and demonstrate its utility for the elucidation of the role of chromatin structure in gene expression.Eugenio MarcoWouter MeulemanJialiang HuangKimberly GlassLuca PinelloJianrong WangManolis KellisGuo-Cheng YuanNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Eugenio Marco Wouter Meuleman Jialiang Huang Kimberly Glass Luca Pinello Jianrong Wang Manolis Kellis Guo-Cheng Yuan Multi-scale chromatin state annotation using a hierarchical hidden Markov model
description	The impact of chromatin structure on gene expression makes it integral to our understanding of developmental and disease processes. Here, the authors introduce a hierarchical hidden Markov model to systematically annotate chromatin states at multiple length scales, and demonstrate its utility for the elucidation of the role of chromatin structure in gene expression.
format	article
author	Eugenio Marco Wouter Meuleman Jialiang Huang Kimberly Glass Luca Pinello Jianrong Wang Manolis Kellis Guo-Cheng Yuan
author_facet	Eugenio Marco Wouter Meuleman Jialiang Huang Kimberly Glass Luca Pinello Jianrong Wang Manolis Kellis Guo-Cheng Yuan
author_sort	Eugenio Marco
title	Multi-scale chromatin state annotation using a hierarchical hidden Markov model
title_short	Multi-scale chromatin state annotation using a hierarchical hidden Markov model
title_full	Multi-scale chromatin state annotation using a hierarchical hidden Markov model
title_fullStr	Multi-scale chromatin state annotation using a hierarchical hidden Markov model
title_full_unstemmed	Multi-scale chromatin state annotation using a hierarchical hidden Markov model
title_sort	multi-scale chromatin state annotation using a hierarchical hidden markov model
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/2004377ed7d24b28b5e7aa6b466a4072
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Multi-scale chromatin state annotation using a hierarchical hidden Markov model

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