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- Title
GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery.
- Authors
Matthew, Sean; Carter, Fin; Cooper, Joshua; Dippel, Matthew; Green, Ethan; Hodges, Samuel; Kidwell, Mason; Nickerson, Dalton; Rumsey, Bryan; Reeve, Jesse; Petzold, Linda R.; Sanft, Kevin R.; Drawerta, Brian
- Abstract
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.
- Subjects
BIOCHEMICAL models; SIMULATION methods &; models; MATHEMATICAL models; SOFTWARE architecture; STOCHASTIC models; PYTHON programming language
- Publication
Letters in Biomathematics, 2023, Vol 10, Issue 1, p87
- ISSN
2373-7867
- Publication type
Article