GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery

Overview

Journal Lett Biomath

Date 2023 Sep 1

PMID 37655179

Authors

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

Affiliations

Soon will be listed here.

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.

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