Beyond Chemical 1D knowledge using Transformers

In the present paper we evaluated efficiency of the recent Transformer-CNN models to predict target properties based on the augmented stereochemical SMILES. We selected a well-known Cliff activity dataset as well as a Dipole moment dataset and compared the effect of three representations for R/S stereochemistry in SMILES... (read more)

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