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OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. / Pfeuffer, Julianus; Bielow, Chris; Wein, Samuel; Jeong, Kyowon; Netz, Eugen; Walter, Axel; Alka, Oliver; Nilse, Lars; Colaianni, Pasquale Domenico; McCloskey, Douglas; Kim, Jihyung; Rosenberger, George; Bichmann, Leon; Walzer, Mathias; Veit, Johannes; Boudaud, Bertrand; Bernt, Matthias; Patikas, Nikolaos; Pilz, Matteo; Startek, Michał Piotr; Kutuzova, Svetlana; Heumos, Lukas; Charkow, Joshua; Sing, Justin Cyril; Feroz, Ayesha; Siraj, Arslan; Weisser, Hendrik; Dijkstra, Tjeerd M.H.; Perez-Riverol, Yasset; Röst, Hannes; Kohlbacher, Oliver; Sachsenberg, Timo.
I:
Nature Methods, Bind 21, Nr. 3, 2024, s. 365–367.
Publikation: Bidrag til tidsskrift › Letter › Forskning › fagfællebedømt
Harvard
Pfeuffer, J, Bielow, C, Wein, S, Jeong, K, Netz, E, Walter, A, Alka, O, Nilse, L, Colaianni, PD, McCloskey, D, Kim, J, Rosenberger, G, Bichmann, L, Walzer, M, Veit, J, Boudaud, B, Bernt, M, Patikas, N, Pilz, M, Startek, MP
, Kutuzova, S, Heumos, L, Charkow, J, Sing, JC, Feroz, A, Siraj, A, Weisser, H, Dijkstra, TMH, Perez-Riverol, Y, Röst, H, Kohlbacher, O & Sachsenberg, T 2024, '
OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data',
Nature Methods, bind 21, nr. 3, s. 365–367.
https://doi.org/10.1038/s41592-024-02197-7APA
Pfeuffer, J., Bielow, C., Wein, S., Jeong, K., Netz, E., Walter, A., Alka, O., Nilse, L., Colaianni, P. D., McCloskey, D., Kim, J., Rosenberger, G., Bichmann, L., Walzer, M., Veit, J., Boudaud, B., Bernt, M., Patikas, N., Pilz, M., ... Sachsenberg, T. (2024).
OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data.
Nature Methods,
21(3), 365–367.
https://doi.org/10.1038/s41592-024-02197-7Vancouver
Pfeuffer J, Bielow C, Wein S, Jeong K, Netz E, Walter A o.a.
OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data.
Nature Methods. 2024;21(3):365–367.
https://doi.org/10.1038/s41592-024-02197-7Author
Pfeuffer, Julianus ; Bielow, Chris ; Wein, Samuel ; Jeong, Kyowon ; Netz, Eugen ; Walter, Axel ; Alka, Oliver ; Nilse, Lars ; Colaianni, Pasquale Domenico ; McCloskey, Douglas ; Kim, Jihyung ; Rosenberger, George ; Bichmann, Leon ; Walzer, Mathias ; Veit, Johannes ; Boudaud, Bertrand ; Bernt, Matthias ; Patikas, Nikolaos ; Pilz, Matteo ; Startek, Michał Piotr ; Kutuzova, Svetlana ; Heumos, Lukas ; Charkow, Joshua ; Sing, Justin Cyril ; Feroz, Ayesha ; Siraj, Arslan ; Weisser, Hendrik ; Dijkstra, Tjeerd M.H. ; Perez-Riverol, Yasset ; Röst, Hannes ; Kohlbacher, Oliver ; Sachsenberg, Timo. / OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. I: Nature Methods. 2024 ; Bind 21, Nr. 3. s. 365–367.
Bibtex
@article{9b26258bfcd94fb696c3f79b27c3a576,
title = "OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data",
author = "Julianus Pfeuffer and Chris Bielow and Samuel Wein and Kyowon Jeong and Eugen Netz and Axel Walter and Oliver Alka and Lars Nilse and Colaianni, {Pasquale Domenico} and Douglas McCloskey and Jihyung Kim and George Rosenberger and Leon Bichmann and Mathias Walzer and Johannes Veit and Bertrand Boudaud and Matthias Bernt and Nikolaos Patikas and Matteo Pilz and Startek, {Micha{\l} Piotr} and Svetlana Kutuzova and Lukas Heumos and Joshua Charkow and Sing, {Justin Cyril} and Ayesha Feroz and Arslan Siraj and Hendrik Weisser and Dijkstra, {Tjeerd M.H.} and Yasset Perez-Riverol and Hannes R{\"o}st and Oliver Kohlbacher and Timo Sachsenberg",
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-W{\"u}rttemberg. A.S. and A.F. are part of the MSCA-ITN-2020 PROTrEIN project, which received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation program under the Marie Sk{\l}odowska-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). ",
year = "2024",
doi = "10.1038/s41592-024-02197-7",
language = "English",
volume = "21",
pages = "365–367",
journal = "Nature Methods",
issn = "1548-7091",
publisher = "nature publishing group",
number = "3",
}
RIS
TY - JOUR
T1 - OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data
AU - Pfeuffer, Julianus
AU - Bielow, Chris
AU - Wein, Samuel
AU - Jeong, Kyowon
AU - Netz, Eugen
AU - Walter, Axel
AU - Alka, Oliver
AU - Nilse, Lars
AU - Colaianni, Pasquale Domenico
AU - McCloskey, Douglas
AU - Kim, Jihyung
AU - Rosenberger, George
AU - Bichmann, Leon
AU - Walzer, Mathias
AU - Veit, Johannes
AU - Boudaud, Bertrand
AU - Bernt, Matthias
AU - Patikas, Nikolaos
AU - Pilz, Matteo
AU - Startek, Michał Piotr
AU - Kutuzova, Svetlana
AU - Heumos, Lukas
AU - Charkow, Joshua
AU - Sing, Justin Cyril
AU - Feroz, Ayesha
AU - Siraj, Arslan
AU - Weisser, Hendrik
AU - Dijkstra, Tjeerd M.H.
AU - Perez-Riverol, Yasset
AU - Röst, Hannes
AU - Kohlbacher, Oliver
AU - Sachsenberg, Timo
N1 - 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).
PY - 2024
Y1 - 2024
U2 - 10.1038/s41592-024-02197-7
DO - 10.1038/s41592-024-02197-7
M3 - Letter
C2 - 38366242
AN - SCOPUS:85185108195
VL - 21
SP - 365
EP - 367
JO - Nature Methods
JF - Nature Methods
SN - 1548-7091
IS - 3
ER -
