Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition
deposit · DDA · 1 version · 8 papers
Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition. DDA vs DIA comparison
| Kind | deposit |
| Acquisition | DDA |
| Organisms | Homo sapiens (human) |
Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition. DDA vs DIA comparison
Versions
as deposited
released 2023-10-27
Where it lives:
- PRIDE · PXD046453
Trained on by (3)
- False discovery rate control for trustworthy AI-based de novo peptide sequencing (2026) preprint as deposited
- Advancing Proteomic Analyses with Graph-Based Deep Learning: Protein Inference and DIA De Novo Peptide Sequencing (2025) thesis as deposited
- Disentangling the Complex Multiplexed DIA Spectra in De Novo Peptide Sequencing (2024) preprint as deposited
Evaluated on by (4)
- MassNet: billion-scale AI-ready mass spectral corpus empowering scalable deep learning in proteomics (2026) peer-reviewed as deposited
- False discovery rate control for trustworthy AI-based de novo peptide sequencing (2026) preprint as deposited
- Advancing Proteomic Analyses with Graph-Based Deep Learning: Protein Inference and DIA De Novo Peptide Sequencing (2025) thesis as deposited
- Disentangling the Complex Multiplexed DIA Spectra in De Novo Peptide Sequencing (2024) preprint as deposited
Used by (4)
Papers that ran on it where the catalog has not recorded whether for training or for evaluation.
- Learning from tandem mass spectra at scale with a self-supervised foundation model for proteomics (2026) preprint as deposited
- A living proteomics benchmark for comprehensive evaluation of deep learning-based de novo peptide sequencing tools (2026) preprint as deposited
- MassNet: billion-scale AI-friendly mass spectral corpus enables robust de novo peptide sequencing (2025) preprint as deposited
- De Novo sequencing-assisted homology search for DIA data analysis enables low abundance peptide variants discovery (2025) preprint as deposited
Methods on these papers (6)
- DIANovo algorithm
- DIAVariant algorithm
- FDR control for AI-based de novo sequencing post-processor
- InstaNovo-FM algorithm
- Living proteomics benchmark benchmark
- XuanjiNovo algorithm
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.