• Corpus ID: 210701879

Graph Attentional Autoencoder for Anticancer Hyperfood Prediction

@article{Gonzalez2020GraphAA,
  title={Graph Attentional Autoencoder for Anticancer Hyperfood Prediction},
  author={Guadalupe Gonzalez and Shunwang Gong and Ivan Laponogov and Kirill A. Veselkov and Michael M. Bronstein},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.05724}
}
Recent research efforts have shown the possibility to discover anticancer drug-like molecules in food from their effect on protein-protein interaction networks, opening a potential pathway to disease-beating diet design. We formulate this task as a graph classification problem on which graph neural networks (GNNs) have achieved state-of-the-art results. However, GNNs are difficult to train on sparse low-dimensional features according to our empirical evidence. Here, we present graph augmented… 

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