"RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De ..."

Cheng-Hao Liu et al. (2022)

> Home

Details and statistics

DOI: 10.1021/ACS.JCIM.1C01476

access: closed

type: Journal Article

metadata version: 2022-06-13

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/jcisd/LiuKJWBS22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/jcisd/LiuKJWBS22
Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler:
RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software. J. Chem. Inf. Model. 62(10): 2293-2300 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.