## Prospr: The Protein Structure Prediction Toolbox
<p align="center">
<img src="docs/source/_static/prospr_logo.png" alt="Prospr's logo" width="496" height="308">
</p>
<div align="center">
[](https://prospr.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/pre-commit/pre-commit)
</div>
**Creator:** Okke van Eck
Prospr is a universal toolbox for protein structure prediction within the
HP-model.
At the core, Prospr offers an easy-to-use Protein data structure, which can be
used to simulate protein folding.
It also offers algorithms, datasets and visualization functions.
The Protein data structure tracks many properties when folding the protein.
This includes tracking the number of conformation changes, which makes it
possible to determine the relative hardness of a protein for a specific
algorithm.
This allows for a fair comparison between different algorithms.
So far, only square lattices are supported in n-dimensions.
The amino acids can only be placed in the corners of the squares and have to be
one unit distance away from the previously placed amino acid.
The Python package is based on a C++ core, which gives Prospr its high
performance.
The C++ core is made available as a separate zip file to facilitate
high-performance computing applications.
See the C++ core section below for direct links to the core.
## Installation and documentation
This package can simply be installed via pip by running:
```bash
pip install prospr
```
A quickstart and reference documentation can be found at
[prospr.readthedocs.io](https://prospr.readthedocs.io).
The PDF version of the complete documentation can be found
[here](https://prospr.readthedocs.io/_/downloads/en/latest/pdf/).
## Archives
All the C++ core files and datasets are also available as compressed archives.
See the subsections below for direct links.
### C++ core
All the core code which prospr runs on, is available as a compressed archive.
The folder `archives` contains a [.zip](archives/prospr_core.zip) and
a [.tar.gz](archives/prospr_core.tar.gz) archive.
### Datasets
The complete collection of datasets is available as a compressed archive in the
`archives` folder. It is available as a [.zip](archives/prospr_data.zip) and a
[.tar.tz](archives/prospr_data.tar.gz) archive.
## Future work
This toolbox could be used for other protein folding problems within discrete
models.
It would be a great extension to support different models by creating a modular
amino acid.
## License
The used license is the GNU LESSER GENERAL PUBLIC LICENSE.
A copy can be found in the [LICENSE](LICENSE) file on GitHub.
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"description": "## Prospr: The Protein Structure Prediction Toolbox\n<p align=\"center\">\n <img src=\"docs/source/_static/prospr_logo.png\" alt=\"Prospr's logo\" width=\"496\" height=\"308\"> \n</p>\n<div align=\"center\">\n\n\n\n\n[](https://prospr.readthedocs.io/en/latest/?badge=latest)\n[](https://github.com/pre-commit/pre-commit)\n\n</div>\n\n**Creator:** Okke van Eck\n\nProspr is a universal toolbox for protein structure prediction within the\nHP-model.\nAt the core, Prospr offers an easy-to-use Protein data structure, which can be\nused to simulate protein folding.\nIt also offers algorithms, datasets and visualization functions.\nThe Protein data structure tracks many properties when folding the protein.\nThis includes tracking the number of conformation changes, which makes it\npossible to determine the relative hardness of a protein for a specific \nalgorithm.\nThis allows for a fair comparison between different algorithms.\n\nSo far, only square lattices are supported in n-dimensions.\nThe amino acids can only be placed in the corners of the squares and have to be\none unit distance away from the previously placed amino acid.\n\nThe Python package is based on a C++ core, which gives Prospr its high\nperformance.\nThe C++ core is made available as a separate zip file to facilitate\nhigh-performance computing applications.\nSee the C++ core section below for direct links to the core.\n\n## Installation and documentation\nThis package can simply be installed via pip by running:\n```bash\npip install prospr\n```\nA quickstart and reference documentation can be found at\n[prospr.readthedocs.io](https://prospr.readthedocs.io).\nThe PDF version of the complete documentation can be found\n[here](https://prospr.readthedocs.io/_/downloads/en/latest/pdf/).\n\n## Archives\nAll the C++ core files and datasets are also available as compressed archives.\nSee the subsections below for direct links.\n\n### C++ core\nAll the core code which prospr runs on, is available as a compressed archive.\nThe folder `archives` contains a [.zip](archives/prospr_core.zip) and\na [.tar.gz](archives/prospr_core.tar.gz) archive.\n\n### Datasets\nThe complete collection of datasets is available as a compressed archive in the\n`archives` folder. It is available as a [.zip](archives/prospr_data.zip) and a\n[.tar.tz](archives/prospr_data.tar.gz) archive.\n\n## Future work\nThis toolbox could be used for other protein folding problems within discrete\nmodels.\nIt would be a great extension to support different models by creating a modular\namino acid.\n\n## License\nThe used license is the GNU LESSER GENERAL PUBLIC LICENSE.\nA copy can be found in the [LICENSE](LICENSE) file on GitHub.\n",
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