<div align="center">
<h1>qsarKit</h1>
[](https://opensource.org/licenses/MIT)
[](https://pysd.readthedocs.io/en/latest/development/development_index.html)
[](https://pypi.python.org/pypi/pysd/)
[](https://hits.seeyoufarm.com)
[](https://github.com/tahiri-lab/QSAR/releases)
</div>
<h2 align="center">⚛️ QSAR Predictive Modeling for Evaluating Contaminant Transfer</h2>
<details open>
<summary>Table of Contents</summary>
<ol>
<li>
<a href="#about-the-project">About the project</a>
</li>
<li>
<a href="#installation">Installation</a>
</li>
<li>
<a href="#use-cases">Use cases</a>
</li>
<li>
<a href="#tutorials">Tutorials</a>
</li>
<li>
<a href="#documentation">Documentation</a>
</li>
<li>
<a href="#contact">Contact</a>
</li>
</ol>
</details>
<a id="about-the-project"></a>
# 📝 About the project
`qsarKit` is a Python package that offers robust predictive modeling using QSAR for evaluating the transfer of
environmental contaminants in breast milk. Developed by the dedicated team led by
Professor [Nadia Tahiri](https://tahirinadia.github.io/) at the University of Sherbrooke in Quebec, Canada. This
open-source integrates multiple predictive models, provides synthetic data generation via GANs, and is tailored for
researchers and health professionals.
<a id="installation"></a>
# ⚒️ Installation
[Miniconda](https://docs.conda.io/projects/miniconda/en/latest/miniconda-install.html) is used to handle the environment
dependencies.
Once ```miniconda``` is installed, the environment can be created and activated with the following commands:
```bash
conda env create -f environment.yaml
conda activate qsar_env
```
If you encounter any issues activating the environment, try sourcing the Conda script first and then retry activation:
```bash
source ~/miniconda3/bin/activate qsar_env
```
or if you installed Anaconda instead of Miniconda:
```bash
source ~/anaconda3/bin/activate qsar_env
```
⚠️ We currently only support Python 3.10 due to some dependencies that are not yet compatible with Python 3.11+. We will
update the package as soon as the dependencies are updated.
<a id="use-cases"></a>
# 🚀 Use cases
The `qsarKit` package can be encapsulated in other applications or used as a standalone package.
You can refer to the tutorials on how to use the package functionalities, or use the package as a standalone application.
To perform a quick test, you can run the package with only one model by executing the following command:
```bash
python main.py --config ridge.yaml --output results/
```
For a more generic way of running the package as a standalone application, you can execute the following command by
specifying the ```<config_file>``` (path to the `YAML` configuration file) and ```<output_dir>``` (path to the output
directory).
```bash
python main.py --config <config_file> --output <output_dir>
```
Both arguments are optional. If not provided, the default values are ```config/compare_all_models.yaml```
and ```results/```, respectively.
We can also generate synthetic data using GANs by including the ```gan``` flag in the configuration file.
You can explore examples of the different options provided by the package in the ```config/``` folders.
And you can refer to the ```gan``` tutorial.
<a id="tutorials"></a>
# 📚 Tutorials
We provide several tutorials to help you get started with the package. You can find them in the ```tutorials/``` folder.
You can explore the ```tutorials/models/```, ```tutorials/gan/```, and ```tutorials/preprocessing/``` folders to learn
more about the different functionalities of the package.
<a id="documentation"></a>
# 📖 Documentation
You can also refer to the [documentation](https://tahiri-lab.github.io/QSAR/) for more details.
We generated the documentation using [Sphinx](https://www.sphinx-doc.org/en/master/). To generate the documentation
locally, you can run the following command:
Linux/Mac:
```bash
cd docs/
make html
```
Windows:
```bash
cd docs/
.\make.bat html
```
The documentation will be generated in the ```docs/build/html/``` folder. You can open the ```index.html``` file in your
browser to view the documentation.
<a id="contact"></a>
# 📧 Contact
Please email us at: <Nadia.Tahiri@USherbrooke.ca> for any questions or feedback.
[Go to Top](#about-the-project)
Raw data
{
"_id": null,
"home_page": "https://github.com/tahiri-lab/QSAR",
"name": "qsarKit",
"maintainer": null,
"docs_url": null,
"requires_python": "==3.10.*",
"maintainer_email": null,
"keywords": "QSAR, Machine Learning, Chemoinformatics, Drug Discovery, Models, Metrics",
"author": "Tahiri Lab",
"author_email": "Tahiri Lab <nadia.tahiri@usherbrooke.ca>",
"download_url": "https://files.pythonhosted.org/packages/82/f9/6ec71a232d1eac0fcbfd0e4b5df7b43156e384b24636514f6af826405647/qsarKit-0.0.1.tar.gz",
"platform": null,
"description": "<div align=\"center\">\n<h1>qsarKit</h1>\n\n[](https://opensource.org/licenses/MIT)\n[](https://pysd.readthedocs.io/en/latest/development/development_index.html)\n[](https://pypi.python.org/pypi/pysd/)\n[](https://hits.seeyoufarm.com)\n[](https://github.com/tahiri-lab/QSAR/releases)\n\n</div>\n\n<h2 align=\"center\">\u269b\ufe0f QSAR Predictive Modeling for Evaluating Contaminant Transfer</h2>\n\n<details open>\n <summary>Table of Contents</summary>\n <ol>\n <li>\n <a href=\"#about-the-project\">About the project</a>\n </li>\n <li>\n <a href=\"#installation\">Installation</a>\n </li>\n <li>\n <a href=\"#use-cases\">Use cases</a>\n </li>\n <li>\n <a href=\"#tutorials\">Tutorials</a>\n </li>\n <li>\n <a href=\"#documentation\">Documentation</a>\n </li>\n <li>\n <a href=\"#contact\">Contact</a>\n </li>\n </ol>\n</details>\n\n<a id=\"about-the-project\"></a>\n\n# \ud83d\udcdd About the project\n\n`qsarKit` is a Python package that offers robust predictive modeling using QSAR for evaluating the transfer of\nenvironmental contaminants in breast milk. Developed by the dedicated team led by\nProfessor [Nadia Tahiri](https://tahirinadia.github.io/) at the University of Sherbrooke in Quebec, Canada. This\nopen-source integrates multiple predictive models, provides synthetic data generation via GANs, and is tailored for\nresearchers and health professionals.\n\n<a id=\"installation\"></a>\n\n# \u2692\ufe0f Installation\n\n[Miniconda](https://docs.conda.io/projects/miniconda/en/latest/miniconda-install.html) is used to handle the environment\ndependencies.\n\nOnce ```miniconda``` is installed, the environment can be created and activated with the following commands:\n\n```bash\nconda env create -f environment.yaml\nconda activate qsar_env\n```\n\nIf you encounter any issues activating the environment, try sourcing the Conda script first and then retry activation:\n\n```bash\nsource ~/miniconda3/bin/activate qsar_env\n```\n\nor if you installed Anaconda instead of Miniconda:\n```bash\n\nsource ~/anaconda3/bin/activate qsar_env\n```\n\n\u26a0\ufe0f We currently only support Python 3.10 due to some dependencies that are not yet compatible with Python 3.11+. We will\nupdate the package as soon as the dependencies are updated.\n\n<a id=\"use-cases\"></a>\n\n# \ud83d\ude80 Use cases\n\nThe `qsarKit` package can be encapsulated in other applications or used as a standalone package.\nYou can refer to the tutorials on how to use the package functionalities, or use the package as a standalone application.\nTo perform a quick test, you can run the package with only one model by executing the following command:\n\n```bash\npython main.py --config ridge.yaml --output results/\n```\n\nFor a more generic way of running the package as a standalone application, you can execute the following command by\nspecifying the ```<config_file>``` (path to the `YAML` configuration file) and ```<output_dir>``` (path to the output\ndirectory).\n\n```bash\npython main.py --config <config_file> --output <output_dir>\n```\n\nBoth arguments are optional. If not provided, the default values are ```config/compare_all_models.yaml```\nand ```results/```, respectively.\n\nWe can also generate synthetic data using GANs by including the ```gan``` flag in the configuration file.\nYou can explore examples of the different options provided by the package in the ```config/``` folders.\nAnd you can refer to the ```gan``` tutorial.\n\n<a id=\"tutorials\"></a>\n\n# \ud83d\udcda Tutorials\n\nWe provide several tutorials to help you get started with the package. You can find them in the ```tutorials/``` folder.\nYou can explore the ```tutorials/models/```, ```tutorials/gan/```, and ```tutorials/preprocessing/``` folders to learn\nmore about the different functionalities of the package.\n\n<a id=\"documentation\"></a>\n\n# \ud83d\udcd6 Documentation\n\nYou can also refer to the [documentation](https://tahiri-lab.github.io/QSAR/) for more details.\n\nWe generated the documentation using [Sphinx](https://www.sphinx-doc.org/en/master/). To generate the documentation\nlocally, you can run the following command:\n\nLinux/Mac:\n```bash\ncd docs/\nmake html\n```\n\nWindows:\n```bash\ncd docs/\n.\\make.bat html\n```\n\nThe documentation will be generated in the ```docs/build/html/``` folder. You can open the ```index.html``` file in your\nbrowser to view the documentation.\n\n<a id=\"contact\"></a>\n\n# \ud83d\udce7 Contact\n\nPlease email us at: <Nadia.Tahiri@USherbrooke.ca> for any questions or feedback.\n\n[Go to Top](#about-the-project)\n",
"bugtrack_url": null,
"license": null,
"summary": "A Python package that offers robust predictive modeling using QSAR for evaluating the transfer of environmental contaminants in breast milk. It integrates multiple predictive models, provides synthetic data generation via GANs, and is tailored for researchers and health professionals.",
"version": "0.0.1",
"project_urls": {
"Homepage": "https://github.com/tahiri-lab/QSAR"
},
"split_keywords": [
"qsar",
" machine learning",
" chemoinformatics",
" drug discovery",
" models",
" metrics"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "a839ae98aeb34efad79c97b4082723dbdf2b5c8c7273135cb7016aa30504e0a6",
"md5": "160c307e81f5b941dad808ac6a9d1a21",
"sha256": "b3864ef4740789e70bbc3df11241aff802a5e9606b39e69c6aefa5ce035d2e41"
},
"downloads": -1,
"filename": "qsarKit-0.0.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "160c307e81f5b941dad808ac6a9d1a21",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "==3.10.*",
"size": 36683,
"upload_time": "2024-05-08T15:53:36",
"upload_time_iso_8601": "2024-05-08T15:53:36.077296Z",
"url": "https://files.pythonhosted.org/packages/a8/39/ae98aeb34efad79c97b4082723dbdf2b5c8c7273135cb7016aa30504e0a6/qsarKit-0.0.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "82f96ec71a232d1eac0fcbfd0e4b5df7b43156e384b24636514f6af826405647",
"md5": "dc79051063c2bd363a218cc1eed0f74f",
"sha256": "3ec5273b917999dccb67b48130270bb9dd07b9bd533c874837dd057aff0d26a9"
},
"downloads": -1,
"filename": "qsarKit-0.0.1.tar.gz",
"has_sig": false,
"md5_digest": "dc79051063c2bd363a218cc1eed0f74f",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "==3.10.*",
"size": 28954,
"upload_time": "2024-05-08T15:53:39",
"upload_time_iso_8601": "2024-05-08T15:53:39.312671Z",
"url": "https://files.pythonhosted.org/packages/82/f9/6ec71a232d1eac0fcbfd0e4b5df7b43156e384b24636514f6af826405647/qsarKit-0.0.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-05-08 15:53:39",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "tahiri-lab",
"github_project": "QSAR",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "qsarkit"
}
JSON
