Corpus ID: 220403613

Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions

@article{Ryou2020GraphNN,
  title={Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions},
  author={Serim Ryou and Michael R Maser and Alexander Cui and Travis J. DeLano and Yisong Yue and S. Reisman},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.04275}
}
  • Serim Ryou, Michael R Maser, +3 authors S. Reisman
  • Published 2020
  • Computer Science, Mathematics
  • ArXiv
  • We present a systematic investigation using graph neural networks (GNNs) to model organic chemical reactions. To do so, we prepared a dataset collection of four ubiquitous reactions from the organic chemistry literature. We evaluate seven different GNN architectures for classification tasks pertaining to the identification of experimental reagents and conditions. We find that models are able to identify specific graph features that affect reaction conditions and lead to accurate predictions… CONTINUE READING

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