Applications of PDEs and Stochastic Modeling to Protein Transport in Cell Biology

TL;DR

This paper explores how PDEs and stochastic models can be used to understand the complex intracellular transport of proteins, providing insights into cellular organization and protein sorting.

Contribution

It introduces the application of PDEs and stochastic models specifically to protein transport in cell biology, highlighting their usefulness in analyzing cellular dynamics.

Findings

PDEs effectively model spatiotemporal protein dynamics.

Stochastic models capture state-switching behavior of proteins.

Mathematical models offer insights into cellular organization.

Abstract

Intracellular transport processes are essential to the healthy development of many organisms as well as more generally to healthy cellular function. The complex dynamics and interactions between protein molecules and filaments on different time and spatial scales generate many opportunities for mathematical modeling and analysis that can provide insights into protein sorting and overall cellular organization. Systems of advection-reaction-diffusion partial differential equations and stochastic state-switching particle models are especially useful in understanding spatiotemporal protein dynamics inside cells.