"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models

scientific article published on 22 June 2018

"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1039/C8SC02339E
P932PMC publication ID6053976
P698PubMed publication ID30090297

P50authorPhilippe SchwallerQ87708901
Teodoro LainoQ114271251
P2093author name stringThéophile Gaudin
Costas Bekas
Dávid Lányi
P2860cites workSMILES, a chemical language and information system. 1. Introduction to methodology and encoding rulesQ28090714
A Short Review of Chemical Reaction Database Systems, Computer-Aided Synthesis Design, Reaction Prediction and Synthetic FeasibilityQ38916874
Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction.Q45948705
Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural NetworksQ48024105
P275copyright licenseCreative Commons Attribution-NonCommercial 3.0 UnportedQ18810331
P6216copyright statuscopyrightedQ50423863
P433issue28
P304page(s)6091-6098
P577publication date2018-06-22
P1433published inChemical ScienceQ2962267
P1476title"Found in Translation": predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models
P478volume9

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