PXD010382 is an
original dataset announced via ProteomeXchange.
Dataset Summary
Title | High quality MS/MS spectrum prediction for data-dependent and -independent acquisition data analysis |
Description | Peptide fragmentation spectra are routinely predicted in the interpretation of mass spectrometry-based proteomics data. Unfortunately, the generation of fragment ions is not well enough understood to estimate fragment ion intensities accurately. Here, we demonstrate that machine learning can predict peptide fragmentation patterns in mass spectrometers with accuracy within the uncertainty of the measurements. Moreover, analysis of our models reveals that peptide fragmentation depends on long-range interactions within a peptide sequence. We illustrate the utility of our models by applying them to the analysis of both data-dependent and data-independent acquisition datasets. In the former case, we observe a significant increase in the total number of peptide identifications at fixed false discovery rate. In the latter case we demonstrate that the use of predicted MS/MS spectra is equivalent to the use of spectra from experimentallibraries, indicating that fragmentation libraries for proteomics are becoming obsolete. |
HostingRepository | PRIDE |
AnnounceDate | 2024-10-22 |
AnnouncementXML | Submission_2024-10-22_04:51:58.381.xml |
DigitalObjectIdentifier | |
ReviewLevel | Peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Unsupported dataset by repository |
PrimarySubmitter | Shivani Tiwary |
SpeciesList | scientific name: Homo sapiens (Human); NCBI TaxID: 9606; |
ModificationList | monohydroxylated residue; iodoacetamide derivatized residue |
Instrument | Q Exactive |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
0 | 2018-07-11 06:49:48 | ID requested | |
1 | 2019-03-13 03:01:20 | announced | |
2 | 2019-04-23 08:38:28 | announced | Updated project metadata. |
3 | 2019-05-29 04:06:27 | announced | Updated project metadata. |
⏵ 4 | 2024-10-22 04:52:04 | announced | 2024-10-22: Updated project metadata. |
Publication List
10.1038/s41592-019-0427-6; |
Tiwary S, Levy R, Gutenbrunner P, Salinas Soto F, Palaniappan KK, Deming L, Berndl M, Brant A, Cimermancic P, Cox J, High-quality MS/MS spectrum prediction for data-dependent and data-independent acquisition data analysis. Nat Methods, 16(6):519-525(2019) [pubmed] |
Keyword List
curator keyword: Technical, Biological |
submitter keyword: Deep learning, DIA, Machine learning , Intensity prediction, Andromeda |
Contact List
Juergen Cox; Peter Cimermancic |
contact affiliation | Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany; Verily Life Sciences, 269 E Grand Ave, South San Francisco, CA 94080, USA |
contact email | cox@biochem.mpg.de |
lab head | |
Shivani Tiwary |
contact affiliation | Max Planck Institute of Biochemistry |
contact email | shivani@biochem.mpg.de |
dataset submitter | |
Full Dataset Link List
Dataset FTP location
NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2019/03/PXD010382 |
PRIDE project URI |
Repository Record List
[ + ]
[ - ]
- PRIDE
- PXD010382
- Label: PRIDE project
- Name: High quality MS/MS spectrum prediction for data-dependent and -independent acquisition data analysis