Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-21895-w
Abstract: Organic synthesis remains a major challenge in drug discovery. Although a plethora of machine learning models have been proposed as solutions in the literature, they suffer from being opaque black-boxes. It is neither clear if… read more here.
Keywords: machine learning; learning models; reaction prediction; reaction ... See more keywords
Root-aligned SMILES: a tight representation for chemical reaction prediction
Sign Up to like & getrecommendations! Published in 2022 at "Chemical Science"
DOI: 10.1039/d2sc02763a
Abstract: Chemical reaction prediction, involving forward synthesis and retrosynthesis prediction, is a fundamental problem in organic synthesis. A popular computational paradigm formulates synthesis prediction as a sequence-to-sequence translation problem, where the typical SMILES is adopted for… read more here.
Keywords: chemical reaction; root aligned; aligned smiles; prediction ... See more keywords
Improving Chemical Reaction Prediction with Unlabeled Data
Sign Up to like & getrecommendations! Published in 2022 at "Molecules"
DOI: 10.3390/molecules27185967
Abstract: Predicting products of organic chemical reactions is useful in chemical sciences, especially when one or more reactants are new organics. However, the performance of traditional learning models heavily relies on high-quality labeled data. In this… read more here.
Keywords: chemical reaction; prediction; unlabeled data; reaction prediction ... See more keywords