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Model Reduction of Multicellular Communication Systems via Singular Perturbation: Sender Receiver Systems

Taishi Kotsuka, Enoch Yeung

TL;DR

Numerical results show the reduced model closely matches the full dynamics while enabling scalable simulation of large cell populations, and singular perturbation theory is used to reduce the model to a finite dimensional multiagent network.

Abstract

We investigate multicellular sender receiver systems embedded in hydrogel beads, where diffusible signals mediate interactions among heterogeneous cells. Such systems are modeled by PDE ODE couplings that combine three dimensional diffusion with nonlinear intracellular dynamics, making analysis and simulation challenging. We show that the diffusion dynamics converges exponentially to a quasi steady spatial profile and use singular perturbation theory to reduce the model to a finite dimensional multiagent network. A closed form communication matrix derived from the spherical Green's function captures the effective sender receiver coupling. Numerical results show the reduced model closely matches the full dynamics while enabling scalable simulation of large cell populations.

Model Reduction of Multicellular Communication Systems via Singular Perturbation: Sender Receiver Systems

TL;DR

Numerical results show the reduced model closely matches the full dynamics while enabling scalable simulation of large cell populations, and singular perturbation theory is used to reduce the model to a finite dimensional multiagent network.

Abstract

We investigate multicellular sender receiver systems embedded in hydrogel beads, where diffusible signals mediate interactions among heterogeneous cells. Such systems are modeled by PDE ODE couplings that combine three dimensional diffusion with nonlinear intracellular dynamics, making analysis and simulation challenging. We show that the diffusion dynamics converges exponentially to a quasi steady spatial profile and use singular perturbation theory to reduce the model to a finite dimensional multiagent network. A closed form communication matrix derived from the spherical Green's function captures the effective sender receiver coupling. Numerical results show the reduced model closely matches the full dynamics while enabling scalable simulation of large cell populations.

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