Predicting stimulation-dependent enhancer-promoter interactions from ChIP-Seq time course data

We have developed a machine learning approach to predict stimulation-dependent enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured o...

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Detalhes bibliográficos
Publicado no:PeerJ
Main Authors: Dzida, Tomasz, Iqbal, Mudassar, Charapitsa, Iryna, Reid, George, Stunnenberg, Henk, Matarese, Filomena, Grote, Korbinian, Honkela, Antti, Rattray, Magnus
Formato: Artigo
Idioma:Inglês
Publicado em: PeerJ Inc. 2017
Assuntos:
Bioinformatics
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5623311/
https://ncbi.nlm.nih.gov/pubmed/28970965
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj.3742
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