Here is a list of interesting projects that would be nice to have identified because they have been previously used in deep-learning training algorithms:
DDA datasets:
[ ] PXD008034: 12
[ ] PXD000269: 79
[ ] PXD024364: Global detection of human variants and isoforms by deep proteome sequencing
[ ] PXD004977: 42
[ ] PXD001608: 60
[ ] PXD002549: 89
[ ] PXD002452: 179
[ ] PXD001636: 60
[ ] PXD004087: 72
[ ] PXD001695: 234
[ ] PXD002785: 22
[ ] PXD000955: 196
[ ] PXD003472: 36
[ ] PXD001865: 144
[ ] PXD002607: 36 (De novo PTM Peaks)
[ ] PXD002908: 40
[ ] MSV000085230
[ ] PXD031812: 32
[ ] PXD003002: 24
[ ] PXD004276: 136
[ ] PXD003189: 64
[ ] PXD003583: 30
[ ] PXD004321: 42
[ ] PXD005126: 45
[ ] PXD002912: 90
DeepMass Manuscript:
[ ] PXD002908: 40
[ ] PXD002912: 90
[ ] PXD003668: 101
[ ] PXD001608: 60
[ ] PXD004977: 42
[ ] PXD002549: 89
[ ] PXD002452: 179
[ ] PXD000955: 196
[ ] PXD001865: 144
[ ] PXD001695: 234
[ ] PXD026436: 3
[ ] PXD039809: 36
[ ] PXD019483: 128
Prosit:
[ ] PXD010871: 8 (This dataset do not contains spectra DDA)
[ ] PXD034056: 6 (This dataset do not contains spectra)
Here is a list of interesting projects that would be nice to have identified because they have been previously used in deep-learning training algorithms:
DDA datasets:
DeepMass Manuscript:
Prosit:
ProteomeTools:
Ion mobility:
PTMs - ubiquitinome:
PTMs - phospho:
DIA- Pposphoproteomics:
DIA:
Single cell dataset:
HLA Datasets:
Tumor, Cell line dataset:
Big datasets, tissue, species proteome: