OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data

Publikation: Bidrag til tidsskriftLetterForskningfagfællebedømt

  • Julianus Pfeuffer
  • Chris Bielow
  • Samuel Wein
  • Kyowon Jeong
  • Eugen Netz
  • Axel Walter
  • Oliver Alka
  • Lars Nilse
  • Pasquale Domenico Colaianni
  • Douglas McCloskey
  • Jihyung Kim
  • George Rosenberger
  • Leon Bichmann
  • Mathias Walzer
  • Johannes Veit
  • Bertrand Boudaud
  • Matthias Bernt
  • Nikolaos Patikas
  • Matteo Pilz
  • Michał Piotr Startek
  • Lukas Heumos
  • Joshua Charkow
  • Justin Cyril Sing
  • Ayesha Feroz
  • Arslan Siraj
  • Hendrik Weisser
  • Tjeerd M.H. Dijkstra
  • Yasset Perez-Riverol
  • Hannes Röst
  • Oliver Kohlbacher
  • Timo Sachsenberg
OriginalsprogEngelsk
TidsskriftNature Methods
Vol/bind21
Udgave nummer3
Sider (fra-til)365–367
ISSN1548-7091
DOI
StatusUdgivet - 2024

Bibliografisk note

Funding Information:
C.B. was in part supported by the Chan Zuckerberg EOSS program (179). J.P. was funded by Forschungscampus MODAL (project grant 3FO18501). K.J., E.N. and T.S. were supported by the Ministry of Science, Research and Arts Baden-Württemberg. A.S. and A.F. are part of the MSCA-ITN-2020 PROTrEIN project, which received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No: 956148. J.C. was funded by the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-164) and supported by the Ontario Graduate Scholarship. J.C.S. was funded by the European Research Area Network Personalized Medicine Cofund (PerProGlio). A.W. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation TRR 261/1,Z03). S.W. was supported by de.NBI (031A535A), Analytics for Biologics (H2020-MSCA-ITN-2017), the EU H2020 project EPIC-XS (H2020-INFRAIA), TRR (TP Z03), and TUE.AI. S.K. was funded by Horizon 2020 under grant agreement No 686070. M.P.S. was funded by Polish National Science Centre grant no. 2017/26/D/ST6/00304. Y.P.-R. acknowledges funding from EMBL core funding, Wellcome grants (208391/Z/17/Z, 223745/Z/21/Z), and the EU H2020 project EPIC-XS (823839).

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