INCAWrapper:INCA 的 Python 封装器,用于无缝导入、导出和处理数据。

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2024-07-04 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae100
Matthias Mattanovich, Viktor Hesselberg-Thomsen, Annette Lien, Dovydas Vaitkus, Victoria Sara Saad, Douglas McCloskey
{"title":"INCAWrapper:INCA 的 Python 封装器,用于无缝导入、导出和处理数据。","authors":"Matthias Mattanovich, Viktor Hesselberg-Thomsen, Annette Lien, Dovydas Vaitkus, Victoria Sara Saad, Douglas McCloskey","doi":"10.1093/bioadv/vbae100","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>INCA is a powerful tool for metabolic flux analysis, however, import and export of data and results can be tedious and limit the use of INCA in automated workflows.</p><p><strong>Results: </strong>The INCAWrapper enables the use of INCA purely through Python, which allows the use of INCA in common data science workflows.</p><p><strong>Availability and implementation: </strong>The INCAWrapper is implemented in Python and can be found at https://github.com/biosustain/incawrapper. It is freely available under an MIT License. To run INCA, the user needs their own MATLAB and INCA licenses. INCA is freely available for noncommercial use at mfa.vueinnovations.com.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245311/pdf/","citationCount":"0","resultStr":"{\"title\":\"INCAWrapper: a Python wrapper for INCA for seamless data import, -export, and -processing.\",\"authors\":\"Matthias Mattanovich, Viktor Hesselberg-Thomsen, Annette Lien, Dovydas Vaitkus, Victoria Sara Saad, Douglas McCloskey\",\"doi\":\"10.1093/bioadv/vbae100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Motivation: </strong>INCA is a powerful tool for metabolic flux analysis, however, import and export of data and results can be tedious and limit the use of INCA in automated workflows.</p><p><strong>Results: </strong>The INCAWrapper enables the use of INCA purely through Python, which allows the use of INCA in common data science workflows.</p><p><strong>Availability and implementation: </strong>The INCAWrapper is implemented in Python and can be found at https://github.com/biosustain/incawrapper. It is freely available under an MIT License. To run INCA, the user needs their own MATLAB and INCA licenses. INCA is freely available for noncommercial use at mfa.vueinnovations.com.</p>\",\"PeriodicalId\":72368,\"journal\":{\"name\":\"Bioinformatics advances\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245311/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioinformatics advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/bioadv/vbae100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

动机INCA 是一种强大的代谢通量分析工具,然而,数据和结果的导入和导出可能很繁琐,限制了 INCA 在自动化工作流中的使用:INCAWrapper可让用户纯粹通过Python使用INCA,从而在常见的数据科学工作流中使用INCA:INCAWrapper 使用 Python 实现,可在 https://github.com/biosustain/incawrapper 上找到。它在 MIT 许可下免费提供。要运行 INCA,用户需要自己的 MATLAB 和 INCA 许可证。INCA 可在 mfa.vueinnovations.com 免费用于非商业用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
INCAWrapper: a Python wrapper for INCA for seamless data import, -export, and -processing.

Motivation: INCA is a powerful tool for metabolic flux analysis, however, import and export of data and results can be tedious and limit the use of INCA in automated workflows.

Results: The INCAWrapper enables the use of INCA purely through Python, which allows the use of INCA in common data science workflows.

Availability and implementation: The INCAWrapper is implemented in Python and can be found at https://github.com/biosustain/incawrapper. It is freely available under an MIT License. To run INCA, the user needs their own MATLAB and INCA licenses. INCA is freely available for noncommercial use at mfa.vueinnovations.com.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.60
自引率
0.00%
发文量
0
期刊最新文献
motifbreakR v2: expanded variant analysis including indels and integrated evidence from transcription factor binding databases. TransAnnot-a fast transcriptome annotation pipeline. PatchProt: hydrophobic patch prediction using protein foundation models. Accelerating protein-protein interaction screens with reduced AlphaFold-Multimer sampling. CAPTVRED: an automated pipeline for viral tracking and discovery from capture-based metagenomics samples.
×
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