Bayesian inference of PolII dynamics over the exclusion process

09/10/2021
by   Massimo Cavallaro, et al.
0

Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of 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 in the hydrodynamic limit, 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.

READ FULL TEXT
research
03/28/2018

Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models

We introduce a Bayesian framework for inference with a supervised versio...
research
11/04/2022

Fully Bayesian inference for latent variable Gaussian process models

Real engineering and scientific applications often involve one or more q...
research
09/27/2018

Adaptive Gaussian process surrogates for Bayesian inference

We present an adaptive approach to the construction of Gaussian process ...
research
05/20/2021

Nonlinear Hawkes Process with Gaussian Process Self Effects

Traditionally, Hawkes processes are used to model time–continuous point ...
research
02/06/2014

Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models - a Gentle Tutorial

In this tutorial we explain the inference procedures developed for the s...
research
02/27/2017

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings

We introduce a novel kernel that models input-dependent couplings across...
research
01/14/2020

Analysis of Bayesian Inference Algorithms by the Dynamical Functional Approach

We analyze the dynamics of an algorithm for approximate inference with l...

Please sign up or login with your details

Forgot password? Click here to reset