Ontology highlight
ABSTRACT:
SUBMITTER: Coley CW
PROVIDER: S-EPMC6335848 | biostudies-other | 2019 Jan
REPOSITORIES: biostudies-other
Chemical science 20181126 2
We present a supervised learning approach to predict the products of organic reactions given their reactants, reagents, and solvent(s). The prediction task is factored into two stages comparable to manual expert approaches: considering possible sites of reactivity and evaluating their relative likelihoods. By training on hundreds of thousands of reaction precedents covering a broad range of reaction types from the patent literature, the neural model makes informed predictions of chemical reactiv ...[more]