About
AIdsorb is a Python package for deep learning on molecular point clouds.
AIdsorb aims to provide a simple, easy-to-use and reproduce interface for:
📥 Creating molecular point clouds
🤖 Training DL algorithms on molecular point clouds
Why molecular point clouds?
A molecular point cloud, being essentially a set of atomic positions, atomic numbers and any additional information, provides a natural and efficient way to represent molecular structures and chemical systems in a machine understandable format. This in turns allows us to perform DL directly on raw structural information, removing the need for manual feature extraction.
The above point cloud represents IRMOF-1. You can hover over the figure to play with it.
TODO
Enable users to make predictions from the command line.
Enable users to fine-tune models trained on large data.
This might require the usage of PyTorch Geometric.
Add more featurization options. These should be fast!
Contributing
We welcome contributions from the community! Please read our Contributing Guide before submitting PRs or opening issues.
Citing
Please refer to the citation file or click the citation button on GitHub.
@article{Sarikas2024,
title = {Gas adsorption meets geometric deep learning: points, set and match},
volume = {14},
ISSN = {2045-2322},
url = {http://dx.doi.org/10.1038/s41598-024-76319-8},
DOI = {10.1038/s41598-024-76319-8},
number = {1},
journal = {Scientific Reports},
publisher = {Springer Science and Business Media LLC},
author = {Sarikas, Antonios P. and Gkagkas, Konstantinos and Froudakis, George E.},
year = {2024},
month = nov
}
License
AIdsorb is released under the GNU General Public License v3.0 only.
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