Probability & stochastic processes in biology: models, methods, and community (Part 2)

Organizers:

Eric Foxall (UBC Okanagan), Jinsu Kim, POSTECH and Linh Huynh, Dartmouth College

Description:

Mathematical biology has a long and rich history of physics-based models and methods. These include both explicitly physics-based models, such as mechanical models of cell wall geometry and molecular models of protein translation and folding, and those inspired by physics, such as interacting particle system models in ecology and epidemiology, to name just a few. In some cases, existing approaches are not optimal for the study of biochemical systems due to various issues including the curse of dimensionality, infinite state spaces, and uncertainty in model structure. Methods from probability theory, especially new methods developed specifically for the study of biological phenomena, can simplify and strengthen our analysis and understanding of these phenomena. In this minisymposium, which has two parts due to significant interest in the subject, we gather researchers from diverse backgrounds and fields of study to exchange ideas, models and methods. The intention is to foster communication and collaboration in the study of stochastic processes across all of biology, and especially to avail researchers of recent developments that could be fruitful in unexpected areas of application.

Diversity Statement:

Our minisymposium, 'Probability & stochastic processes in biology: models, methods, and community,' is committed to fostering a diverse and inclusive environment in mathematical biology. This minisymposium is organized to serve as a platform for building connections among researchers with diverse backgrounds, expertise, interests, and career stages who are working at the intersection of stochastic processes and biology.