mgktools

Name	mgktools JSON
Version	3.1.0 JSON
	download
home_page	None
Summary	Marginalized Graph Kernel Library for Molecular Property Prediction
upload_time	2025-01-14 17:54:28
maintainer	None
docs_url	None
author	None
requires_python	>=3.9
license	MIT
keywords	chemistry machine learning molecular property prediction marginalized graph kernel drug discovery
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # mgktools
Python Package using marginalized graph kernel (MGK) to predict molecular properties.

## Installation
Suggested Package Versions:
Python>=3.9, GCC==11.2, CUDA==11.7.
```
pip install git+https://gitlab.com/Xiangyan93/graphdot.git@feature/xy
pip install mgktools
```

## Hyperparameters
[hyperparameters](https://github.com/Xiangyan93/mgktools/tree/main/mgktools/hyperparameters) contains the JSON files that
define the hyperparameters for MGK.

## Related work
* [Predicting Single-Substance Phase Diagrams: A Kernel Approach on Graph Representations of Molecules](https://pubs.acs.org/doi/full/10.1021/acs.jpca.1c02391)
* [A Comparative Study of Marginalized Graph Kernel and Message-Passing Neural Network](https://pubs.acs.org/doi/full/10.1021/acs.jcim.1c01118)
* [Interpretable Molecular Property Predictions Using Marginalized Graph Kernels](https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c00396)

            

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