activity
20162026
collaborators

6 papers

math.NA2026

Finite element approximation of the enthalpy formulation for Stefan problems on evolving surfaces

Philip J. Herbert, Thomas Sales, Chandrasekhar Venkataraman

We propose, and analyse, a spatially discrete evolving surface finite element method for the approximation of the enthalpy formulation of the two-phase Stefan problem posed on an e…

math.AP2024

Free boundary limits of coupled bulk-surface models for receptor-ligand interactions on evolving domains

Amal Alphonse, Diogo Caetano, Charles M. Elliott +1

We derive various novel free boundary problems as limits of a coupled bulk-surface reaction-diffusion system modelling ligand-receptor dynamics on evolving domains. These limiting…

q-bio.CB2023

Linking discrete and continuous models of cell birth and migration

W. Duncan Martinson, Alexandria Volkening, Markus Schmidtchen +2

Self-organisation of individuals within large collectives occurs throughout biology. Mathematical models can help elucidate the individual-level mechanisms behind these dynamics, b…

q-bio.CB2023

An individual-based model to explore the impact of psychological stress on immune infiltration into tumour spheroids

Emma Leschiera, Gheed Al-Hity, Melanie S. Flint +4

In recent in vitro experiments on co-culture between breast tumour spheroids and activated immune cells, it was observed that the introduction of the stress hormone cortisol result…

math.AP2018

Multiscale analysis and simulation of a signalling process with surface diffusion

Mariya Ptashnyk, Chandrasekhar Venkataraman

We present and analyse a model for cell signalling processes in biological tissues. The model includes diffusion and nonlinear reactions on the cell surfaces, and both inter- and i…

q-bio.QM2016

A Bayesian approach to parameter identification with an application to Turing systems

Eduard Campillo-Funollet, Chandrasekhar Venkataraman, Anotida Madzvamuse

We present a Bayesian methodology for infinite as well as finite dimensional parameter identification for partial differential equation models. The Bayesian framework provides a ri…