John Carlo graduated from the University of Warwick with an MMath in 2024. His research project in 4^th year was in numerical analysis, studying summation-by-parts finite difference operators where he investigated different methods for generating them, and how they can be applied to various PDEs. At Bath, he hopes to move into mathematical biology for his PhD and wants to gain an understanding of stochastic systems and their applications to biological processes.

Outside of maths, John Carlo enjoys playing the piano (to the misfortune of anyone listening), and board games, particularly cooperative ones.

Research project title:
Theoretical and Experimental Applications of the Multi-Stage Model for Cell Proliferation

Supervisor(s):
Kit Yates, Cameron Smith

Project description:
Understanding cell proliferation is fundamental in many biological contexts, including cancer growth, wound healing, and protein copy number distribution. As such, accurate predictions of cell population dynamics are essential. The cell cycle governs how individual cells grow, replicate their DNA, and divide, making it central to understanding cell proliferation. However, common approaches to simulating the cell cycle often rely on the simplifying assumption that cell cycle times follow an exponential distribution. For a fixed mean cell cycle time, proliferation under the assumption of exponentially distributed cell cycle times leads to an overestimation of cell numbers. In this project, we aim to address these limitations by exploring multi-stage models for the cell cycle, which provide a more realistic representation of cell cycle time distributions. 

We will investigate the multi-stage representation of the cell cycle in spatially extended, on-lattice models that incorporate volume exclusion. By varying the mechanisms through which cells progress through the cell cycle, for example by allowing them to respond to their local environment, we aim to develop a biologically realistic framework for understanding how different factors influence population-level dynamics. We will then apply this framework to explain experimental observations of heritable factors between parent and daughter cells, as well as to facilitate inference of true cell cycle times in settings where volume exclusion plays a critical role.