Acknowledgements
================

Funding
-------

This work was supported by the German Cancer Research Center (DKFZ) through
a doctoral fellowship and by the Deparatment of Neuropathology Heidelberg.

Institutional support
---------------------

ProteoPy was developed at:

- **Department of Neuropathology**, Institute of Pathology, University Hospital
  Heidelberg, Germany
- **German Cancer Research Center (DKFZ)**, Heidelberg, Germany
- **German Consortium for Translational Cancer Research (DKTK)**, Heidelberg,
  Germany

We thank the following research groups for providing the scientific
environment in which ProteoPy was developed:

- The **Bludau Lab** and the **Bioinformatics group** within the
  Department of Neuropathology, University Hospital Heidelberg
- The `Gerstung Lab <https://www.dkfz.de/kuenstliche-intelligenz-in-der-onkologie>`_ at the
  German Cancer Research Center (DKFZ), Heidelberg

Inspiration
-----------

ProteoPy's API design draws direct inspiration from the
`scanpy <https://scanpy.readthedocs.io/>`_ and
`muon <https://muon.readthedocs.io/>`_ ecosystems. By adopting their
modular syntax (``pp``, ``tl``, ``pl``) and AnnData-centric workflow,
ProteoPy aims to provide a familiar and accessible interface for
researchers already working within the single-cell and multi-omics
community. We are grateful to the original authors and contributors of
scanpy — in particular `Fabian Theis <https://github.com/theislab>`_ and
the `Theis Lab <https://www.helmholtz-munich.de/en/icb/research-groups/theis-lab>`_
— and of muon — notably
`Danila Bredikhin <https://github.com/gtca>`_ and the
`Stegle Lab <https://www.embl.org/groups/stegle/>`_ at EMBL and DKFZ
— for creating open,
well-designed frameworks that have shaped how the community interacts
with high-dimensional biological data.

Software dependencies
---------------------

ProteoPy builds upon the excellent work of many open-source projects:

- `NumPy <https://numpy.org/>`_ and `SciPy <https://scipy.org/>`_ for numerical computing
- `pandas <https://pandas.pydata.org/>`_ for data manipulation
- `AnnData <https://anndata.readthedocs.io/>`_ for annotated data structures
- `scanpy <https://scanpy.readthedocs.io/>`_ for single-cell analysis integration
- `Matplotlib <https://matplotlib.org/>`_ and `Seaborn <https://seaborn.pydata.org/>`_ for visualization
- `scikit-learn <https://scikit-learn.org/>`_ for machine learning utilities

We are grateful to the developers and maintainers of these projects for their
contributions to the scientific Python ecosystem.

Contact
-------

For correspondence regarding ProteoPy, please contact:

**Isabell Bludau**

Email: isabell.bludau@med.uni-heidelberg.de