Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  High-quality MS/MS spectrum prediction for data-dependent and data-independent acquisition data analysis

Tiwary, S., Levy, R., Gutenbrunner, P., Salinas Soto, F., Palaniappan, K. K., Deming, L., et al. (2019). High-quality MS/MS spectrum prediction for data-dependent and data-independent acquisition data analysis. Nature methods, 16(6), 519-525. doi:10.1038/s41592-019-0427-6.

Item is

Basisdaten

einblenden: ausblenden:
Genre: Zeitschriftenartikel

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Tiwary, Shivani1, Autor           
Levy, Roie2, Autor
Gutenbrunner, Petra1, Autor           
Salinas Soto, Favio1, Autor           
Palaniappan, Krishnan K.2, Autor
Deming, Laura2, Autor
Berndl, Marc2, Autor
Brant, Arthur2, Autor
Cimermancic, Peter2, Autor
Cox, Jürgen1, Autor           
Affiliations:
1Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              
2external, ou_persistent22              

Inhalt

einblenden:
ausblenden:
Schlagwörter: PROTEIN SECONDARY STRUCTURE; MASS-SPECTROMETRY; PEPTIDE; DISSOCIATION; FRAGMENTATIONBiochemistry & Molecular Biology;
 Zusammenfassung: Peptide fragmentation spectra are routinely predicted in the interpretation of mass-spectrometry-based proteomics data. However, the generation of fragment ions has not been understood well enough for scientists 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 measurement. 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 q-value-dependent increase in the total number of peptide identifications. In the latter case, we confirm that the use of predicted tandem mass spectrometry spectra is nearly equivalent to the use of spectra from experimental libraries.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2019
 Publikationsstatus: Erschienen
 Seiten: 9
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISI: 000469455200021
DOI: 10.1038/s41592-019-0427-6
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden: ausblenden:
Projektname : -
Grant ID : 686547
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)
Projektname : GA ERC-2012-SyG_318987–ToPAG
Grant ID : 318987
Förderprogramm : Funding Programme 7 (FP7)
Förderorganisation : European Commission (EC)
Projektname : Marie Skłodowska-Curie European Training Network TEMPERA
Grant ID : 722606
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)

Quelle 1

einblenden:
ausblenden:
Titel: Nature methods
  Andere : Nature methods
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: New York, NY : Nature Pub. Group
Seiten: - Band / Heft: 16 (6) Artikelnummer: - Start- / Endseite: 519 - 525 Identifikator: ISSN: 1548-7091
CoNE: https://pure.mpg.de/cone/journals/resource/111088195279556