Nature Communications (Feb 2021)

Deep learning the collisional cross sections of the peptide universe from a million experimental values

  • Florian Meier,
  • Niklas D. Köhler,
  • Andreas-David Brunner,
  • Jean-Marc H. Wanka,
  • Eugenia Voytik,
  • Maximilian T. Strauss,
  • Fabian J. Theis,
  • Matthias Mann

DOI
https://doi.org/10.1038/s41467-021-21352-8
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 12

Abstract

Read online

Proteomics has been advanced by algorithms that can predict different peptide features, but predicting peptide collisional cross sections (CCS) has remained challenging. Here, the authors measure over one million CCS values of tryptic peptides and develop a deep learning model for peptide CCS prediction.