no code implementations • 23 Jan 2024 • Muhan Ma, Juraj Szavits-Nossan, Abhyudai Singh, Ramon Grima
Our results delineate the region of parameter space where conventional models give qualitatively incorrect results and provide insight into how the number of processing stages, e. g. the number of rate-limiting steps in initiation, splicing and mRNA degradation, shape stochastic gene expression by modulation of molecular memory.
no code implementations • 6 Jul 2023 • Juraj Szavits-Nossan, Ramon Grima
Stochastic models of gene expression are typically formulated using the chemical master equation, which can be solved exactly or approximately using a repertoire of analytical methods.
no code implementations • 11 Apr 2023 • Juraj Szavits-Nossan, Ramon Grima
Here we construct a model of gene expression describing promoter switching between inactive and active states, binding of RNA polymerases in the active state, their stochastic movement including steric interactions along the gene, and their unbinding leading to a mature transcript that subsequently decays.
