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...
Enregistré dans:
Auteurs principaux: | Eugenio Marco, Wouter Meuleman, Jialiang Huang, Kimberly Glass, Luca Pinello, Jianrong Wang, Manolis Kellis, Guo-Cheng Yuan |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2017
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/2004377ed7d24b28b5e7aa6b466a4072 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
A hidden Markov model for lymphatic tumor progression in the head and neck
par: Roman Ludwig, et autres
Publié: (2021) -
Publisher Correction: A hidden Markov model for lymphatic tumor progression in the head and neck
par: Roman Ludwig, et autres
Publié: (2021) -
Off-chip prefetching based on Hidden Markov Model for non-volatile memory architectures.
par: Adrián Lamela, et autres
Publié: (2021) -
A new method for inferring hidden markov models from noisy time sequences.
par: David Kelly, et autres
Publié: (2012) -
Functional annotation of hierarchical modularity.
par: Kanchana Padmanabhan, et autres
Publié: (2012)