Opportunities for Data-Driven Modelling in Cell and Developmental Biology

Date: Friday 25th Sep 2026

Abstract

Advances in imaging and experimental technologies are generating increasingly rich quantitative data describing cell and tissue dynamics. These data create new opportunities to move beyond calibrating predefined mechanistic models towards learning aspects of model structure directly from observations. Hybrid approaches, including universal differential equations and biologically-informed neural networks, provide one route to combining mechanistic knowledge with flexible data-driven components, but also raise fundamental questions about how the resulting models should be interpreted and analysed.

In this talk, I will present recent work exploring data-driven modelling in cell and developmental biology, with a particular focus on developing mathematical tools that parallel those routinely used for classical mechanistic models. I will consider questions including identifiability and uncertainty, the extraction of interpretable dynamical structure, and the analysis of learned models. Using examples from collective cell behaviour, I will illustrate both the opportunities offered by these approaches and some of the challenges that arise when moving from fitting biological data to recovering and interrogating the mechanisms that generated them.

Ruth's Bio:

Ruth Baker is Professor of Applied Mathematics and an Affiliated Principal Investigator at the Institute of Developmental and Regenerative Medicine, University of Oxford. Her research sits at the interface of applied mathematics and the life sciences, developing mathematical and computational approaches to understand complex biological systems and data. She is the recipient of several major honours, including the Whitehead Prize of the London Mathematical Society and a Royal Society Wolfson Research Merit Award, and is currently Chair of the SIAM Life Sciences Activity Group.