Metadata-Version: 2.4
Name: deepmolecularnetwork
Version: 0.2.0
Summary: A deep learning framework for QSAR/QSPR modeling with 3D voxels, tabular descriptors, and molecular representations
Author-email: Giuseppe Marco Randazzo <gmrandazzo@gmail.com>
License: GPL-3.0-or-later
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.22.0
Requires-Dist: scipy>=1.8.0
Requires-Dist: scikit-learn>=1.0.0
Requires-Dist: matplotlib>=3.5.0
Requires-Dist: h5py>=3.6.0
Requires-Dist: pillow>=9.0.0
Provides-Extra: keras2
Requires-Dist: tensorflow-cpu<2.16.0,>=2.13.0; extra == "keras2"
Requires-Dist: keras<3.0.0,>=2.13.0; extra == "keras2"
Requires-Dist: tensorboard>=2.13.0; extra == "keras2"
Provides-Extra: keras3
Requires-Dist: tensorflow-cpu>=2.16.0; extra == "keras3"
Requires-Dist: keras>=3.0.0; extra == "keras3"
Requires-Dist: tensorboard>=2.16.0; extra == "keras3"
Provides-Extra: test
Requires-Dist: pytest>=7.0.0; extra == "test"
Requires-Dist: coverage>=6.0.0; extra == "test"
Provides-Extra: dev
Requires-Dist: deepmolecularnetwork[test]; extra == "dev"
Dynamic: license-file

# DeepMolecularNetwork

![Page views](https://visitor-badge.glitch.me/badge?page_id=gmrandazzo.DeepMolecularNetwork)

A tool to develop QSAR/QSPR Deep machine learning models.
DeepMolecularNetwork provide a framework to build models with:
  - threedimensional voxel data
  - smiles strings
  - tabular values (i.e. molecular descriptors)

Soon example will follows... stay tuned!


Changelog
=========

September 2019 - First online release


License
=======

DeepMolecularNetwork is distributed under GPLV3 license in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.


To know more in details how the license work please read the file "LICENSE" or
go to "http://www.gnu.org/licenses/lgpl-3.0.html"

DeepMolecularNetwork is written and maintained by Giuseppe Marco Randazzo <grandazzo@gmail.com>


Documentation
=============

TODO


Dependencies
============

TODO


Cite/Acknowledgements
=====================

Please if you use this for commercial please send me a mail with your logo
Acknowledge the github page and the author in your application.
If you use for academic research please cite the original GitHub repository.
