oc6b00219_si_001.pdf (118.73 kB)
Neural Networks for the Prediction of Organic Chemistry Reactions
journal contribution
posted on 2016-10-14, 19:46 authored by Jennifer
N. Wei, David Duvenaud, Alán Aspuru-GuzikReaction 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.