A Biochemical Modeling Framework for Simulation Driven Biological Discovery

  • Sean Matthew
  • Fin Carter University of North Carolina Asheville
  • Joshua Cooper
  • Matthew Dippel
  • Ethan Green
  • Samuel Hodges
  • Mason Kidwell
  • Dalton Nickerson
  • Bryan Rumsey
  • Jesse Reeve
  • Linda R. Petzold
  • Kevin R. Sanft
  • Brian Drawert University of North Carolina Asheville
Keywords: Simulation, Modeling, Stochastic, Hybrid


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 address this need, we present GillesPy2, an open-source framework for building and simulating mathematical and biochemical models. GillesPy2, a major upgrade from the original GillesPy package, is now a stand-alone Python 3 package. 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.

How to Cite
Matthew, Sean, Fin Carter, Joshua Cooper, Matthew Dippel, Ethan Green, Samuel Hodges, Mason Kidwell, Dalton Nickerson, Bryan Rumsey, Jesse Reeve, Linda Petzold, Kevin Sanft, and Brian Drawert. 2023. “GillesPy2”. Letters in Biomathematics 10 (1), 87–103.

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