In our lab at the Francis Crick Institute in London, we develop models of intracellular signalling, communication pathways that exist within individual cells, to discover the fundamental principles for how cells operate and maintain themselves as self-organising life forms.

Intracellular signalling allow cells to process information and respond to external cues, but responses usually vary from cell to cell. This variability drives various biological phenomena, including cell fate decisions and resistance to anti-cancer drugs, and is thus relevant to basic biology and human health.

Our lab uses mathematical models of intracellular signalling and blends them with machine learning approaches to integrate data about the cell, such as its shape, molecular make-up, and the structure of proteins found within. The resulting hybrid models help us understand how regulatory rules emerge, and enables us to predict how these rules might differ from cell to cell. We develop the computational tools to build and train these models and apply them to a range of projects, such as predicting sensitivity to anti-cancer drugs, anticipating cell fate decisions and designing synthetic signalling cascades.