Updated MS²PIP web server supports cutting-edge proteomics applications

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• dc.contributor.author Declercq, Arthur
• dc.contributor.author Bouwmeester, Robbin
• dc.contributor.author Chiva, Cristina
• dc.contributor.author Sabidó Aguadé, Eduard, 1981-
• dc.contributor.author Hirschler, Aurélie
• dc.contributor.author Carapito, Christine
• dc.contributor.author Martens, Lennart
• dc.contributor.author Degroeve, Sven
• dc.contributor.author Gabriels, Ralf
• dc.date.accessioned 2023-11-03T07:36:32Z
• dc.date.available 2023-11-03T07:36:32Z
• dc.date.issued 2023
• dc.description.abstract Interest in the use of machine learning for peptide fragmentation spectrum prediction has been strongly on the rise over the past years, especially for applications in challenging proteomics identification workflows such as immunopeptidomics and the full-proteome identification of data independent acquisition spectra. Since its inception, the MS²PIP peptide spectrum predictor has been widely used for various downstream applications, mostly thanks to its accuracy, ease-of-use, and broad applicability. We here present a thoroughly updated version of the MS²PIP web server, which includes new and more performant prediction models for both tryptic- and non-tryptic peptides, for immunopeptides, and for CID-fragmented TMT-labeled peptides. Additionally, we have also added new functionality to greatly facilitate the generation of proteome-wide predicted spectral libraries, requiring only a FASTA protein file as input. These libraries also include retention time predictions from DeepLC. Moreover, we now provide pre-built and ready-to-download spectral libraries for various model organisms in multiple DIA-compatible spectral library formats. Besides upgrading the back-end models, the user experience on the MS²PIP web server is thus also greatly enhanced, extending its applicability to new domains, including immunopeptidomics and MS3-based TMT quantification experiments. MS²PIP is freely available at https://iomics.ugent.be/ms2pip/.
• dc.description.sponsorship Arthur Declercq, Lennart Martens and Ralf Gabriels acknowledge funding from the Research Foundation Flanders (FWO) [12B7123N, G010023N, G028821N, 1SE3722]; Robbin Bouwmeester acknowledges funding from the Vlaams Agentschap Innoveren en Ondernemen [HBC.2020.2205]; Sven Degroeve and Lennart Martens acknowledge funding from the European Union's Horizon 2020 Programme (H2020-INFRAIA-2018-1) [823839]; Lennart Martens acknowledges funding from the Ghent University Concerted Research Action [BOF21/GOA/033]. Eduard Sabidó and Cristina Chiva acknowledge support from the Spanish Ministry of Science, Innovation and Universities (PID2020-115092GB-I00), “Centro de Excelencia Severo Ochoa 2013-2017”, SEV-2012-0208, and “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2017SGR595). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech). This work has been supported by EPIC-XS, project number 823839, funded by the Horizon 2020 programme of the European Union. Funding for open access charge: the Research Foundation Flanders (FWO) [G028821N].
• dc.format.mimetype application/pdf
• dc.identifier.citation Declercq A, Bouwmeester R, Chiva C, Sabidó E, Hirschler A, Carapito C, Martens L, Degroeve S, Gabriels R. Updated MS²PIP web server supports cutting-edge proteomics applications. Nucleic Acids Res. 2023 Jul 5;51(W1):W338-W342. DOI: 10.1093/nar/gkad335
• dc.identifier.doi http://dx.doi.org/10.1093/nar/gkad335
• dc.identifier.issn 0305-1048
• dc.identifier.uri http://hdl.handle.net/10230/58203
• dc.language.iso eng
• dc.publisher Oxford University Press
• dc.relation.ispartof Nucleic Acids Res. 2023 Jul 5;51(W1):W338-W342
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/823839
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-115092GB-I00
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/823839
• dc.rights © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.other Servidors web
• dc.subject.other Proteòmica
• dc.title Updated MS²PIP web server supports cutting-edge proteomics applications
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion