Sean Matthew, Fin Carter, Joshua Cooper, Matthew Dippel, Ethan Green, Samuel Hodges, Mason Kidwell, Dalton Nickerson, Bryan Rumsey, Jesse Reeve, Linda R. Petzold, Kevin R. Sanft, Brian Drawert
Stochastic modeling has become an essential tool for studying biochemical reaction networks. There is a growing need for user-friendly and feature-complete software for model design and simulation. To satisfy this need, we present GillesPy2, an open-source Python 3 library for building and simulating mathematical and biochemical models. GillesPy2 offers an intuitive interface for robust and reproducible model creation, facilitating rapid and iterative development. In addition to expediting the model creation process, GillesPy2 offers efficient algorithms to simulate stochastic, deterministic, and hybrid stochastic-deterministic models. GillesPy2, an major improvement from the original GillesPy package, is now a stand-alone Python