A Probabilistic Model of Transcription Dynamics applied to Estrogen Signalling in Breast Cancer Cells

ABSTRACT: Gene transcription mediated by RNA polymerase II (pol-II) is a key step in gene expression. The dynamics of pol-II moving along the transcribed region influences the rate and timing of gene expression. In this work we present a probabilistic model of transcription dynamics which is fitted to pol-II occupancy time course data measured using ChIP-Seq. The model can be used to estimate transcription speed and to infer the temporal pol-II activity profile at the gene promoter. Model parameters are determined using either maximum likelihood estimation or via Bayesian inference using Markov chain Monte Carlo sampling. The Bayesian approach provides confidence intervals for parameter estimates and allows the use of priors that capture domain knowledge,

ORGANISM(S): Homo sapiens

SUBMITTER: H.G. Stunnenberg 

PROVIDER: E-GEOD-44800 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress