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

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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Bibliographic Details
Main Authors: Tomasz Dzida, Mudassar Iqbal, Iryna Charapitsa, George Reid, Henk Stunnenberg, Filomena Matarese, Korbinian Grote, Antti Honkela, Magnus Rattray
Format: Article
Language:English
Published: PeerJ Inc. 2017-09-01
Series:PeerJ
Subjects:
Enhancer-promoter interaction
Bayesian classifier
Machine learning
Estrogen receptor
ChIP-Seq
Online Access:https://peerj.com/articles/3742.pdf

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https://peerj.com/articles/3742.pdf

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