x3cflux 3.0.6

is a high-performance simulator for isotopically stationary and non-stationary simulation of isotope labeling experiments. It is build on highly optimized C++ code, made available in Python through pybind11. It comprises the following main functions:

• Read metabolic models and labeling data from standardized FluxML
• Simulation of labeling distributions and data residuals given fluxes and metabolite concentrations
• Fitting and statistical analysis (Frequentist and Bayesian) of ¹³C labeling experiments

13CFLUX is being developed by the Modelling and Simulation group under the supervision of Katharina Nöh at the IBG-1, Forschungszentrum Jülich, Germany.

Installation

The recommended way for practitioners to install 13CFLUX is via pip from the Python Package Index (PyPI). It is recommended to do this in a Python environment. Before installation, you should make sure to have ipopt installed (either directly or by installing cyipopt via conda). Then just run

pip install x3cflux

Documentation

We provide a Read The Docs documentation. Check it out!

Development

The development of 13CFLUX primarily takes place on JuGit, where we have access to powerful continuous integration and a Docker registry. Please report issues and request features only JuGit.

Citation

@article{Stratmann2025,
    author = {Stratmann, Anton and Beyß, Martin and Jadebeck, Johann F and Wiechert, Wolfgang and Nöh, Katharina},
    title = {13CFLUX — Third-generation high-performance engine for isotopically (non)stationary 13C metabolic flux analysis},
    journal = {Bioinformatics},
    pages = {btaf630},
    year = {2025},
    issn = {1367-4811},
    doi = {10.1093/bioinformatics/btaf630},
    url = {https://doi.org/10.1093/bioinformatics/btaf630},
}

Further links

• PyPI: https://pypi.org/project/x3cflux/
• Github Mirror: https://github.com/JuBiotech/13CFLUX