Rare-event sampling of epigenetic landscapes and phenotype transitions.

ABSTRACT: Stochastic simulation has been a powerful tool for studying the dynamics of gene regulatory networks, particularly in terms of understanding how cell-phenotype stability and fate-transitions are impacted by noisy gene expression. However, gene networks often have dynamics characterized by multiple attractors. Stochastic simulation is often inefficient for such systems, because most of the simulation time is spent waiting for rare, barrier-crossing events to occur. We present a rare-event simulation-based method for computing epigenetic landscapes and phenotype-transitions in metastable gene networks. Our computational pipeline was inspired by studies of metastability and barrier-crossing in protein folding, and provides an automated means of computing and visualizing essential stationary a

SUBMITTER: Tse MJ 

PROVIDER: S-EPMC6093701 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature