Speakers
Description
Stochastic methods have recently been used to solve important problems in mathematical biology, from modeling degradation of protective layers in biosensors to separating signal from noise in diagnostic instruments. Deterministic tools like integrodifferential and partial differential equations remain powerful for modeling phenomena like reaction-diffusion processes and tumor growth. In these applications, questions of existence and uniqueness provide the rigorous foundation for reliable simulation. This mini-symposium brings these approaches together through a series of presentations that reveal how theoretical guarantees inform computational methods, and how stochastic models complement deterministic frameworks. Topics span analytical foundations to numerical simulation, connecting theory to experiment across different biological applications.
