MS08 - MFBM-09 Part 4 of 4

Probability & stochastic processes in biology: models, methods, and community (Part 4)

Friday, July 18 at 10:20am

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Note: this minisymposia has multiple sessions. The other sessions are: Part-1 Part-2 and Part-3.

Jinsu Kim (POSTECH), Eric Foxall (The University of British Columbia - Okanagan Campus), 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. Special requirement: Some of our speakers are only available on July 14th. Therefore, we kindly request that our minisymposium be scheduled on July 14th.

Alan Lindsay

University of Notre Dame

"Asymptotic and numerical methods for cellular signaling and directional sensing using extreme statistics"

Diffusive arrivals to membrane surfaces provide cues for cellular decision making, for example when and where to move. In this talk we will describe the advancement of both asymptotic and numerical methodologies to describe and interpret these signals. A particular focus of these new methods are to describe the full time dependent fluxes over the cell surface during signaling processes and extreme statistics. We will show several examples how early arrivals to the cell surface, combined with cellular geometry, can increase the strength and quality of directional signaling.

Jennifer Flegg

University Melbourne

"Investigation of vivax malaria elimination using mass drug administration: A simulation study"

Plasmodium vivax is the most geographically widespread malaria parasite. P. vivax has the ability to remain dormant (as a hypnozoite) in the human liver and subsequently reactivate, which makes control efforts more difficult. Given the majority of P. vivax infections are due to hypnozoite reactivation, targeting the hypnozoite reservoir with a radical cure is crucial for achieving P. vivax elimination. Stochastic effects can strongly influence dynamics when disease prevalence is low or when the population size is small. Hence, it is important to account for this when modelling malaria elimination. We use a stochastic multiscale model of P. vivax transmission to study the impacts of multiple rounds of mass drug administration (MDA) with a radical cure, accounting for superinfection and hypnozoite dynamics. Our results indicate multiple rounds of MDA with a high-efficacy drug are needed to achieve a substantial probability of elimination. This work has the potential to help guide P. vivax elimination strategies by quantifying elimination probabilities for an MDA approach.

Liam Yih

University of British Columbia

"Handling molecular binding under force in coarse-grained simulations of passive nanoscale movers"

Inspired by passive nanoscale movers such as viruses and DNA constructs, we are developing a physics-based framework to study emergent system-level motility from simple receptor-ligand interactions. One major challenge to this work arises from the fact that bond potential well dimensions on the sub-nanometer scale leads to impractically short time-steps in a natural Euler-Maruyama scheme for a force-based model. I will describe our work to extend Steven Andrews' Smoldyn algorithm to our system. One important factor is the addition of external forces acting on these bonds, which can impact Smoldyn parameters. I will also discuss our efforts to quantify parameters with the goal of preserving physical consistency.

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Annual Meeting for the Society for Mathematical Biology, 2025.