Learning to Predict Chemical Reactions

  title={Learning to Predict Chemical Reactions},
  author={Matthew A. Kayala and Chlo{\'e}-Agathe Azencott and Jonathan H. Chen and Pierre Baldi},
  journal={Journal of chemical information and modeling},
  volume={51 9},
Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a… CONTINUE READING
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