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    # PhysioFit
    
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    [![PyPI version](https://badge.fury.io/py/physiofit.svg)](https://badge.fury.io/py/physiofit)
    [![PyPI pyversions](https://img.shields.io/pypi/pyversions/physiofit.svg)](https://pypi.python.org/pypi/physiofit/)
    [![Documentation Status](https://readthedocs.org/projects/physiofit/badge/?version=latest)](http://physiofit.readthedocs.io/?badge=latest)
    
    [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/physiofit/README.html)
    
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    ## What is PhysioFit?
    
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    **PhysioFit is a scientific tool designed to quantify cell growth parameters and uptake & production fluxes**
    
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    Fluxes are estimated using mathematical models by fitting time-course measurements of the concentration of
    cells and extracellular substrates and products. PhysioFit is shipped with some common growth models, and
    additional tailor-made models can be implemented by users.
    
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    It is one of the routine tools that we use at the [MetaSys team](https://www.toulouse-biotechnology-institute.fr/en/poles/equipe-metasys/) 
    and [MetaToul platform](https://www.metabohub.fr/home.html) in functional studies of metabolic systems.
    
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    The code is open-source, and available under a GPLv3 license. Additional information can be found in the following 
    
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    [publication](https://doi.org/10.1101/2023.10.12.561695).
    
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    Detailed documentation can be found online at Read the Docs 
    ([https://physiofit.readthedocs.io/](https://physiofit.readthedocs.io/)).
    
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    ## Key features
    
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       * **calculation of growth rate and extracellular (uptake and production) fluxes**,
    
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       * a set of **steady-state and dynamic models**,
    
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       * **tailor-made models** can be constructed by users,
    
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       * Monte-Carlo sensitivity analysis to **estimate the precision of the calculated fluxes**,
    
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       * **evaluation of the goodness of fit and visual inspection of the fitted curves**,
    
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       * calculation of the Akaike information criterion to **guide users to identify the most appropriate model**,
    
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       * shipped as a **library** with both a **graphical** and a **command line** interface,
       * **open-source, free and easy to install** everywhere where Python 3 and pip run,
    
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       * **biologist-friendly**.
    
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    ## Quick-start
    
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    PhysioFit requires Python 3.9 or higher and run on all platforms.
    
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    Please check [the documentation](https://physiofit.readthedocs.io/en/latest/quickstart.html) for complete
    installation and usage instructions.
    
    Use `pip` to **install PhysioFit from PyPi**:
    
    ```bash
    $ pip install physiofit
    ```
    
    Then, start the graphical interface with:
    
    ```bash
    $ physiofit
    ```
    
    PhysioFit is also available directly from command-line and as a Python library.
    
    ## Bug and feature requests
    If you have an idea on how we could improve PhysioFit please submit a new *issue*
    to [our GitHub issue tracker](https://github.com/MetaSys-LISBP/PhysioFit/issues).
    
    
    ## Developers guide
    ### Contributions
    Contributions are very welcome! :heart:
    
    Please work on your own fork,
    follow [PEP8](https://www.python.org/dev/peps/pep-0008/) style guide,
    and make sure you pass all the tests before a pull request.
    
    ### Local install with pip
    In development mode, do a `pip install -e /path/to/PhysioFit` to install
    locally the development version.
    
    ### Build the documentation locally
    Build the HTML documentation with:
    
    ```bash
    $ cd doc
    $ make html
    ```
    
    The PDF documentation can be built locally by replacing `html` by `latexpdf`
    in the command above. You will need a recent latex installation.
    
    ## How to cite
    
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    PhysioFit: a software to quantify cell growth parameters and extracellular fluxes.
    
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    Le Grégam L., Guitton Y., Bellvert F., Jourdan F., Portais J.C., Millard P.
    
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    bioRxiv preprint, [doi: 10.1101/2023.10.12.561695](https://doi.org/10.1101/2023.10.12.561695)
    
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    ## Authors
    Loïc Le Grégam, Pierre Millard
    
    ## Contact
    :email: legregam@insa-toulouse.fr, millard@insa-toulouse.fr