"AutoPeptideML: a study on how to build more trustworthy peptide ..."

Raúl Fernández-Díaz et al. (2024)

> Home

Details and statistics

DOI: 10.1093/BIOINFORMATICS/BTAE555

access: open

type: Journal Article

metadata version: 2026-02-25

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/bioinformatics/Fernandez-DiazC24
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/bioinformatics/Fernandez-DiazC24
Raúl Fernández-Díaz, Rodrigo Cossio-Pérez, Clement Agoni, Hoang Thanh Lam, Vanessa López, Denis C. Shields:
AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors. Bioinform. 40(9) (2024)

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.