Centre for Mathematical Medicine and Biology Seminar

Ramon Grima (University of Edinburgh)

Noise-induced effects in the dynamics of gene regulatory networks in single cells and tissues

Since-cell experiments show that gene expression and regulation is highly noisy. Mathematical models are hence necessary to understand how cells have evolved mechanisms to ensure robust function through the suppression or exploitation of inherent cellular noise. A key difficulty in studies of this type is the fact that stochastic models of gene regulatory networks are rarely exactly solvable and stochastic simulation is computationally expensive compared to conventional deterministic simulations. In this talk I will summarise our efforts to develop new modelling methodologies which lead to approximate but accurate predictions of the noisy spatial and non-spatial dynamics of gene regulatory systems in a computationally efficient manner. I will describe how using these methods we have identified or further elucidated various noise-induced phenomena relevant to cellular decision making, rhythmicity of intracellular oscillators, cellular memory and cell-cell communication.