GillesPy2:模拟驱动生物发现的生化建模框架。

Q3 Mathematics
Letters in Biomathematics Pub Date : 2023-01-10
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
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引用次数: 0

摘要

随机建模已成为研究生化反应网络的重要工具。对用户友好和功能完整的模型设计和仿真软件的需求日益增长。为了满足这一需求,我们提出了GillesPy2,一个用于构建和模拟数学和生化模型的开源框架。GillesPy2是原始GillesPy包的主要升级,现在是一个独立的Python 3包。GillesPy2提供了一个直观的界面,用于稳健和可重复的模型创建,促进快速迭代开发。除了加快模型创建过程外,GillesPy2还提供了高效的算法来模拟随机、确定性和混合随机-确定性模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery.

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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来源期刊
Letters in Biomathematics
Letters in Biomathematics Mathematics-Statistics and Probability
CiteScore
2.00
自引率
0.00%
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0
审稿时长
14 weeks
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