Mathematical Biology Seminar Ying Zhang, Northeastern University, Friday, January 17, 2025 2:00pm in LCB 323 Novel Particle-Based Stochastic Reaction-Diffusion Models: Advancing T Cell Signaling and Beyond Abstract: Mathematical and computational models play a pivotal role in advancing our understanding of immune responses, complementing traditional experimental research and enabling the formulation of new hypotheses. Over the past decade, extensive experimental studies of T cell signaling pathways have highlighted the significant influence of stochasticity in protein diffusion and reactive interactions on signal transduction. Many detailed particle-based stochastic reaction-diffusion models have been developed to account for these stochastic effects. However, challenges persist in creating accurate and efficient numerical methods for these models, particularly when applied to realistic cellular domains with complex geometries. Additionally, the intricate interplay of competing signals that governs T cell activation and deactivation further complicates the development of simplified models suitable for analytical study. To address these challenges, we developed novel numerical methods that efficiently and accurately approximate solutions to stochastic reaction-diffusion models in complex cellular domains. Leveraging these methods, we investigated T cell signaling and derived coarse-grained models that capture key dynamics while remaining amenable to analytical techniques. These numerical and simplified models offer a powerful framework for studying cellular processes involving thousands of interacting molecules in realistic and biologically relevant geometries, with broad applicability beyond T cell signaling.