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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Detalles Bibliográficos
Autores principales: Dzida, Tomasz, Iqbal, Mudassar, Charapitsa, Iryna, Reid, George, Stunnenberg, Henk, Matarese, Filomena, Grote, Korbinian, Honkela, Antti, Rattray, Magnus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5623311/
https://www.ncbi.nlm.nih.gov/pubmed/28970965
http://dx.doi.org/10.7717/peerj.3742

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5623311/
https://www.ncbi.nlm.nih.gov/pubmed/28970965
http://dx.doi.org/10.7717/peerj.3742

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