Marginalized graph kernel library for molecular property prediction
Project description
# mgktools Python Package using marginalized graph kernel (MGK) to predict molecular properties.
## Installation Suggested Package Versions: Python==3.10, GCC==11.2, CUDA==11.7. ` pip install numpy==1.22.3 git+https://gitlab.com/Xiangyan93/graphdot.git@feature/xy git+https://github.com/bp-kelley/descriptastorus pip install mgktools `
## Usage See [notebooks](https://github.com/Xiangyan93/mgktools/tree/main/notebooks)
## 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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