In this talk, we develop a stochastic individual-based model of phenotypic adaptation through a continuously structured phenotype space. Probabilistically, our model corresponds to common partial differential equation models of phenotypic heterogeneity, allowing us to formulate a likelihood that captures the intrinsic noise ubiquitous to low-cell-count proliferation assays. We apply our...
Single-cell experiments revealed substantial variability in generation times, growth rates, birth and division sizes between genetically identical cells. Understanding how these fluctuations determine the fitness of the population, i.e. its long-term growth rate, is necessary in any quantitative theory of evolution. In this talk, I will present a biologically relevant agent-based model of...
Understanding how cells migrate through confined environments is crucial for elucidating fundamental biological processes, including cancer invasion, immune surveillance, and tissue morphogenesis. The nucleus, as the largest and stiffest cellular organelle, often limits cellular deformability, making it a key factor in navigating narrow pores or highly constrained spaces. In this talk, I will...
A novel trait-structured Keller-Segel model that explores the dynamics of a migrating cell population guided by chemotaxis in response to an external ligand concentration is derived and analysed. Unlike traditional Keller-Segel models, this framework introduces an explicit representation of ligand-receptor bindings on the cell membrane, where the percentage of occupied receptors constitutes...
The complexity of biological systems resides in the stochastic fluctuations and interactions between their many components. Even among genetically identical cells, there exists significant heterogeneity in the expression of mRNAs and proteins. This non-genetic cell-to-cell variability plays a central role in shaping population- and tissue-scale dynamics, influencing proliferation, survival,...
