56 citations · 149 across the 8 of their papers we have counts for
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Solving stochastic gene expression models using queueing theory: a tutorial review
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 meth…
Uncovering the effect of RNA polymerase steric interactions on gene expression noise: analytical distributions of nascent and mature RNA numbers
Juraj Szavits-Nossan, Ramon Grima
The telegraph model is the standard model of stochastic gene expression, which can be solved exactly to obtain the distribution of mature RNA numbers per cell. A modification of th…
Steady-state fluctuations of a genetic feedback loop with fluctuating rate parameters using the unified colored noise approximation
James Holehouse, Abhishek Gupta, Ramon Grima
A common model of stochastic auto-regulatory gene expression describes promoter switching via cooperative protein binding, effective protein production in the active state and dilu…
Small protein number effects in stochastic models of autoregulated bursty gene expression
Chen Jia, Ramon Grima
A stochastic model of autoregulated bursty gene expression by Kumar et al. [Phys. Rev. Lett. 113, 268105 (2014)] has been exactly solved in steady-state conditions under the implic…
Exact solution of stochastic gene expression models with bursting, cell cycle and replication dynamics
Casper H. L. Beentjes, Ruben Perez-Carrasco, Ramon Grima
The bulk of stochastic gene expression models in the literature do not have an explicit description of the age of a cell within a generation and hence they cannot capture events su…
Stochastic modeling of auto-regulatory genetic feedback loops: a review and comparative study
James Holehouse, Zhixing Cao, Ramon Grima
Auto-regulatory feedback loops are one of the most common network motifs. A wide variety of stochastic models have been constructed to understand how the fluctuations in protein nu…