Speaker
Luke De Bretton-Gordon
(University of Oxford)
Description
Understanding how local crowding regulates progression through the cell cycle is central to explaining tissue growth and contact inhibition. We develop a novel model of density-dependent cell-cycle progression using Universal Differential Equations (UDEs), in which transition rates between stages of the cell-cycle are represented by neural networks. This approach preserves key mechanistic features, including the Brownian motion of individual cells and conservation of mass between successive cell-cycle phases, while allowing experimental data of expanding epithelial monolayers to determine how local crowding influences progression through the cell cycle.
Author
Luke De Bretton-Gordon
(University of Oxford)
