Modelling gene regulatory pathways in cells stochastically allows for the analysis of noise in these chemical reaction networks. This is precisely what I am interested in.
Auto-regulation in gene expression (together with Peter Pfaffelhuber)
We have quantified the levels of noise that can be suppressed or promoted by auto-regulation in gene expression, i.e. if for example a protein regulates its own production. We found that a negative feedback (suppression of expression) can reduce the level of noise by a factor of at most 1/2 while a positive feedback (enhancing gene expression) can increase noise infinitely.
Publication: Limits of noise for autoregulated gene expression, Journal of Mathematical Biology (2018) (view online)
Quorum Sensing (together with various people)
Cells talk! One way they do this is by so-called Quorum sensing, a mechanism where cells release small diffusible molecules into the environment that can be sensed by neighboring cells. Typically it is a bistable system that can be in an activated or non-activated state. Together with various colleagues I (i) modeled this mechanism in the bacterium Sinorhizobium meliloti and (ii) studied various mechanisms of how the quorum sensing mechanism itself can be regulated, i.e. switching between the two states.
Multiple regulation mechanisms of bacterial quorum sensing. BIOMATH (2016) (view online)
Modeling quorum sensing in Sinorhizobium meliloti. Int. J. Biomath. Biostat (2013) (pdf)