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Detection of essential genes with Graph Neural Networks on protein-protein interaction networks

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Essential gene detection with Graph Neural Networks

Contains code for: EPGAT: Gene Essentiality Prediction With Graph Attention Networks,
by João Schapke, Anderson Tavares, Mariana Recamonde-Mendoza (https://doi.org/10.1109/tcbb.2021.3054738).

Data used is available at: https://drive.google.com/file/d/18TyM7WvZe5QxGCEAxJUWH0kHmi2fWCxa/view?usp=sharing

To train GAT in a dataset run:
python runners/run_gat.py <OPTIONS>

To see which options are available:
python runners/run_gat.py --help

Example:
python runners/run_gat.py --train --organism human --ppi string --sublocs --expression
This will train and evaluate on the human genome dataset with additional data of gene expression profiles and subcellular localizations information.

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