Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproduc
deposit · 1 version · 2 papers
Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results
| Kind | deposit |
| Organisms | Homo sapiens (human), Mus musculus (mouse) |
Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results
Versions
as deposited
released 2017-10-27
Where it lives:
- PRIDE · PXD005573
Used by (2)
- Learning from tandem mass spectra at scale with a self-supervised foundation model for proteomics (2026) preprint as deposited
- Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning (2019) peer-reviewed as deposited
Methods on these papers (2)
- InstaNovo-FM algorithm
- Prosit adjacent
Taken from the describing links only, so a paper that merely ran a tool on this data does not make that tool a method of it.