Strategic applications of named reactions in organic synthesis: background and detailed mechanisms

By L. Kürti, B. Czako, E. Corey, K. Nicolaou. 2005

376 citations recorded by the source corpus.

Subfields: 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 Molecular Biology

1. Mike Preuss
2. Marwin H. S. Segler
3. Mark P. Waller
4. Sergey I. Nikolenko
5. Connor W. Coley
6. A. Pais
7. Tânia F Cova
8. Ola Engkvist

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. Mark P. Waller
4. A. Pais
5. Tânia F Cova
6. Connor W. Coley
7. Philippe Schwaller
8. Teodoro Laino

Citations in the corpus

• Planning chemical syntheses with deep neural networks and symbolic AI (2017, background): “[5] At each retrosynthetic step, out of thousands of known transformations in modern chemistry, chemists intuitively rank the most promising transformations highly, and do not even actively think about the unreasonable ones.”
• Modelling Chemical Reasoning to Predict Reactions (2016, background): “44,45 Our model was able to identify the wrong products and classify these reactions as not occurring Reagents and catalysts are omitted, since they were not predicted here. in 94% of the cases.”