Speaker
Description
Understanding and accurately describing cell proliferation is a crucial step toward realistic modelling of cancer invasion and progression. We propose a framework for parameter estimation and validation of tissue growth models describing the dynamics of proliferating cell colonies \cite{AMC2026}. By confronting model simulations with experimental data, we assess the ability of these models to reproduce key features of cancer cell proliferation. Particular attention is given to identifying the range of applicability of the models. We also highlight the importance of a rigorous and systematic approach to parameter estimation \cite{TD2025}. Overall, our findings contribute to evaluating whether tissue growth models can provide a reliable foundation for more comprehensive descriptions of cancer progression and for the development of effective therapeutic strategies.
Bibliography
@misc{TD2025,
title={Lipschitz stability for Bayesian inference in porous medium tissue growth models},
author={Tomasz Dębiec and Piotr Gwiazda and Błażej Miasojedow and Katarzyna Ryszewska and Zuzanna Szymańska and Aneta Wróblewska-Kamińska},
year={2025},
eprint={2506.04769},
archivePrefix={arXiv},
primaryClass={math.AP},
url={https://arxiv.org/abs/2506.04769}}
@article{AMC2026,
author = {Gwiazda, Piotr and Kazarnikov, Alexey and Marciniak-Czochra, Anna and Szyma{\'n}ska, Zuzanna},
journal = {Bulletin of Mathematical Biology},
number = {1},
pages = {11},
title = {Beyond Bayesian Inference: The Correlation Integral Likelihood Framework and Gradient Flow Methods for Deterministic Sampling},
volume = {88},
year = {2025}}
