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Title: Bayesian inference of PolII pausing dynamics over exclusion processes Authors:  Massimo Cavallaro - University of Warwick (United Kingdom) [presenting]
Yuexuan Wang - University of Warwick (United Kingdom)
Daniel Hebenstreit - University of Warwick (United Kingdom)
Ritabrata Dutta - Warwick University (United Kingdom)
Abstract: Transcription is a complex phenomenon that allows the conversion of genetic information into phenotype through an enzyme called PolII, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e., the asymmetric exclusion processes (ASEP) in mean-field approximation, assuming a Gaussian process prior for the PolII progression rate as a latent variable. Our framework allows us to infer the speed of PolIIs during transcription, given their spatial distribution whilst avoiding the explicit inversion of the system's dynamics. The results may have implications for the understanding of gene expression and biological noise.