GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery.

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
{"title":"GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery.","authors":"Sean Matthew,&nbsp;Fin Carter,&nbsp;Joshua Cooper,&nbsp;Matthew Dippel,&nbsp;Ethan Green,&nbsp;Samuel Hodges,&nbsp;Mason Kidwell,&nbsp;Dalton Nickerson,&nbsp;Bryan Rumsey,&nbsp;Jesse Reeve,&nbsp;Linda R Petzold,&nbsp;Kevin R Sanft,&nbsp;Brian Drawert","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":"10 1","pages":"87-103"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10470263/pdf/nihms-1921950.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Letters in Biomathematics","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

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.

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
GillesPy2:模拟驱动生物发现的生化建模框架。
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
Letters in Biomathematics
Letters in Biomathematics Mathematics-Statistics and Probability
CiteScore
2.00
自引率
0.00%
发文量
0
审稿时长
14 weeks
期刊最新文献
GillesPy2: A Biochemical Modeling Framework for Simulation Driven Biological Discovery. Welcome to Volume 10 Modeling Seasonal Malaria Transmission: A Methodology Connecting Regional Temperatures to Mosquito and Parasite Developmental Traits Mathematical Analysis and Parameter Estimation of a Two-Patch Zika Model Modeling Assumptions, Mathematical Analysis and Mitigation Through Intervention
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1