OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data
Publikation: Bidrag til tidsskrift › Letter › Forskning › fagfællebedømt
Originalsprog | Engelsk |
---|---|
Tidsskrift | Nature Methods |
Vol/bind | 21 |
Udgave nummer | 3 |
Sider (fra-til) | 365–367 |
ISSN | 1548-7091 |
DOI | |
Status | Udgivet - 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).
ID: 384617783