Speakers
Description
Modern mathematical biology requires moving seamlessly from model construction to highly optimized simulation and deep mathematical analysis. In this first of two sessions, we introduce Catalyst.jl, a domain-specific language and symbolic modeling platform within the Julia SciML ecosystem designed for the rapid, intuitive modeling of complex biological networks. With a special focus on the newly released Catalyst 16, attendees will learn how to construct systems and automatically generate ordinary differential equations (ODEs), stochastic differential equations (SDEs), and jump processes models. We will highlight new Catalyst 16 capabilities such as adding coupled jump-diffusion equations, enabling the simulation of advanced systems like stochastic neuron models and reaction networks that include dynamic, fluctuating, cell volumes. We will also present performance optimization strategies for speeding up simulations.
Complementing basic model construction and simulation, we will demonstrate how Catalyst easily integrates with packages throughout the broader Julia ecosystem. First, we will consider how HomotopyContinuation.jl and Catalyst enable finding all of a model's steady states. Next, we will show how to compute bifurcation diagrams using BifurcationKit.jl. Finally, we will show how such packages can leverage Catalyst’s network analysis functionality, including the automatic detection and computation of conservation laws.
