Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > q-bio > arXiv:2509.23847

Help | Advanced Search

Quantitative Biology > Quantitative Methods

arXiv:2509.23847 (q-bio)
[Submitted on 28 Sep 2025 ]

Title: 13CFLUX - Third-generation high-performance engine for isotopically (non)stationary 13C metabolic flux analysis

Title: 13CFLUX - 第三代用于同位素(非)稳态13C代谢通量分析的高性能引擎

Authors:Anton Stratmann, Martin Beyß, Johann F. Jadebeck, Wolfgang Wiechert, Katharina Nöh
Abstract: 13C-based metabolic flux analysis (13C-MFA) is a cornerstone of quantitative systems biology, yet its increasing data complexity and methodological diversity place high demands on simulation software. We introduce 13CFLUX(v3), a third-generation simulation platform that combines a high-performance C++ engine with a convenient Python interface. The software delivers substantial performance gains across isotopically stationary and nonstationary analysis workflows, while remaining flexible to accommodate diverse labeling strategies and analytical platforms. Its open-source availability facilitates seamless integration into computational ecosystems and community-driven extension. By supporting multi-experiment integration, multi-tracer studies, and advanced statistical inference such as Bayesian analysis, 13CFLUX provides a robust and extensible framework for modern fluxomics research.
Abstract: 基于13C的代谢通量分析(13C-MFA)是定量系统生物学的核心,但其日益增加的数据复杂性和方法多样性对模拟软件提出了更高的要求。我们介绍了13CFLUX(v3),这是一个第三代模拟平台,结合了高性能的C++引擎和便捷的Python接口。该软件在同位素稳态和非稳态分析工作流程中实现了显著的性能提升,同时保持灵活性以适应多种标记策略和分析平台。其开源可用性促进了无缝集成到计算生态系统和社区驱动的扩展中。通过支持多实验集成、多示踪剂研究以及先进的统计推断(如贝叶斯分析),13CFLUX为现代通量组学研究提供了强大且可扩展的框架。
Subjects: Quantitative Methods (q-bio.QM)
Cite as: arXiv:2509.23847 [q-bio.QM]
  (or arXiv:2509.23847v1 [q-bio.QM] for this version)
  https://doi.org/10.48550/arXiv.2509.23847
arXiv-issued DOI via DataCite

Submission history

From: Katharina Nöh [view email]
[v1] Sun, 28 Sep 2025 12:35:59 UTC (3,384 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • HTML (experimental)
  • TeX Source
license icon view license
Current browse context:
q-bio.QM
< prev   |   next >
new | recent | 2025-09
Change to browse by:
q-bio

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号