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
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Acceso en línea:https://doaj.org/article/2004377ed7d24b28b5e7aa6b466a4072
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Sumario: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.