Molecular Transformer for Chemical Reaction Prediction and Uncertainty Estimation

@article{Schwaller2018MolecularTF,
  title={Molecular Transformer for Chemical Reaction Prediction and Uncertainty Estimation},
  author={P. Schwaller and T. Laino and T. Gaudin and P. Bolgar and C. Bekas and Alpha A. Lee},
  journal={ArXiv},
  year={2018},
  volume={abs/1811.02633}
}
Organic synthesis is one of the key stumbling blocks in medicinal chemistry. A necessary yet unsolved step in planning synthesis is solving the forward problem: given reactants and reagents, predict the products. Similar to other works, we treat reaction prediction as a machine translation problem between SMILES strings of reactants-reagents and the products. We show that a multi-head attention Molecular Transformer model outperforms all algorithms in the literature, achieving a top-1 accuracy… Expand
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