title: Neural Networks for the Prediction of Organic Chemistry Reactions.
abstract: Reaction prediction remains one of the major challenges for organic chemistry and is a prerequisite for efficient synthetic planning. It is desirable to develop algorithms that, like humans, "learn" from being exposed to examples of the application of the rules of organic chemistry. We explore the use of neural networks for predicting reaction types, using a new reaction fingerprinting method. We combine this predictor with SMARTS transformations to build a system which, given a set of reagents and reactants, predicts the likely products. We test this method on problems from a popular organic chemistry textbook.
authors: Department of Chemistry and Chemical Biology, Harvard University , Cambridge, Massachusetts 02138, United States.
authors: Jennifer N
authors: JN
authors: Wei
authors: Department of Computer Science, Harvard University , Cambridge, Massachusetts 02138, United States.
authors: David
authors: D
authors: Duvenaud
authors: Department of Chemistry and Chemical Biology, Harvard University , Cambridge, Massachusetts 02138, United States.
authors: Alán
authors: A
authors: Aspuru-Guzik