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.
Publications:
Multiple regulation mechanisms of bacterial quorum sensing. BIOMATH, 2016 (view online)
Modeling quorum sensing in Sinorhizobium meliloti. Int. J. Biomath. Biostat, 2013 (pdf)