We build computational models to unravel the regulatory principles underlying the dynamics of intracellular signalling.
Signalling is intricately regulated by numerous molecular mechanisms and exhibits considerable cell-to-cell variability. Despite this apparent complexity, the resultant cellular decision making is often tightly controlled and simple.
We challenge this paradox by blending machine learning and mathematical modelling. Through this coupling of top down and bottom up approaches, we distill simple, mechanistic explanations how signalling is governed by protein-protein interactions, compartmentalisation, genetic variation and the molecular make-up of cells.