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PXD010382

PXD010382 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleHigh quality MS/MS spectrum prediction for data-dependent and -independent acquisition data analysis
DescriptionPeptide 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.
HostingRepositoryPRIDE
AnnounceDate2024-10-22
AnnouncementXMLSubmission_2024-10-22_04:51:58.381.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterShivani Tiwary
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListmonohydroxylated residue; iodoacetamide derivatized residue
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02018-07-11 06:49:48ID requested
12019-03-13 03:01:20announced
22019-04-23 08:38:28announcedUpdated project metadata.
32019-05-29 04:06:27announcedUpdated project metadata.
42024-10-22 04:52:04announced2024-10-22: 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 affiliationComputational 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 emailcox@biochem.mpg.de
lab head
Shivani Tiwary
contact affiliationMax Planck Institute of Biochemistry
contact emailshivani@biochem.mpg.de
dataset submitter
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Dataset FTP location
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PRIDE project URI
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