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Mathematical Modelling of stem cell differentiation

Graduate: Théo André

My work is divided into two topics. First, we investigate the phenomenon of de novo (Turing-like) pattern formation through the analysis of Reaction-Diffusion-ODE models, focusing on the Diffusion-Driven Instability mechanisms. The second part consists of building a model to describe how neural stem cells achieve dynamical, spatiotemporal, long-term homeostasis in the zebrafish telencephalon, through spatially enriched differential equations.