ML Anthology

Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets (Student Abstract)

Mengying Sun, Fei Wang, Olivier Elemento, Jiayu Zhou
AAAI 2020 pp. 13927-13928
doi:10.1609/AAAI.V34I10.7236 /aaai/2020/sun2020aaai-structure/

Abstract

In this work, we proposed a DDI detection method based on molecular structures using graph convolutional networks and deep sets. We proposed a more discriminative convolutional layer compared to conventional GCN and achieved permutation invariant prediction without losing the capability of capturing complicated interactions.

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Cite

Text

Sun et al. "Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets (Student Abstract)." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I10.7236

Markdown

[Sun et al. "Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets (Student Abstract)." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/sun2020aaai-structure/) doi:10.1609/AAAI.V34I10.7236

BibTeX

@inproceedings{sun2020aaai-structure,
  title     = {{Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets (Student Abstract)}},
  author    = {Sun, Mengying and Wang, Fei and Elemento, Olivier and Zhou, Jiayu},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {13927-13928},
  doi       = {10.1609/AAAI.V34I10.7236},
  url       = {https://mlanthology.org/aaai/2020/sun2020aaai-structure/}
}