Organic synthesis: march of the machines.

By S. Ley, Daniel E. Fitzpatrick, Richard Ingham, R. Myers. 2015

383 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology, Organic Chemistry, Computational Chemistry & Drug Discovery

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Vijay S. Pande
2. Mike Preuss
3. Mark P. Waller
4. Marwin H. S. Segler

In Molecular Biology

1. Mike Preuss
2. Marwin H. S. Segler
3. Mark P. Waller
4. Bharath Ramsundar
5. Vijay S. Pande
6. Joseph Gomes
7. Bowen Liu
8. Chaopeng Shen

In Organic Chemistry

1. Mike Preuss
2. Mark P. Waller
3. Marwin H. S. Segler

In Computational Chemistry & Drug Discovery

1. Mike Preuss
2. Marwin H. S. Segler
3. Vijay S. Pande
4. Mark P. Waller
5. Bowen Liu
6. Joseph Gomes
7. Bharath Ramsundar
8. Chaopeng Shen

Citations in the corpus

• Planning chemical syntheses with deep neural networks and symbolic AI (2017, methodology): “[8–11] To perform CASP, the knowledge that humans “simply learn” has to be transferred into an executable program .”
• Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models (2017, background): “6 In part this is due to these approaches being applicable to only relatively simple target molecules for which expert chemists could readily deduce synthetic plans without assistance.”
• Modelling Chemical Reasoning to Predict Reactions (2016, background): “12 However, we emphasise that the found paths are not a transitive law.”