I lead a research group investigating quantitative control of gene expression at the single-cell level – ranging from epigenetic memory and cellular decision-making to global RNA metabolism in the context of cellular physiology.

Proper control of gene expression underpins the normal development of organisms, and is dysregulated in diseases such as cancer. We seek to better understand which components of a cell are involved in this control, and how they work together. Our fundamental discoveries regarding the normal operation of cells underpin the identification of new disease mechanisms and possible therapeutic targets. We also contribute to the development of new research methodologies and analysis methods for use in drug discovery and diagnostics applications.

We make extensive use of high-throughput microscopy, including highly multiplexed immunofluorescence and RNA fluorescence in situ hybridisation, as well as live-cell imaging and automated image analysis. Together, these approaches enable detailed measurement of quantitative cellular phenotypes (for example, the abundance and localisations of specific proteins or RNAs) across large cell populations. We analyse resulting datasets using data science methods and interpret and explore hypotheses through the development of minimal mathematical models. We complement these image-based experimental approaches with functional genomics experiments (based on next-generation sequencing) and we use perturbation experiments including genome and epigenome-editing to test specific hypotheses.