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Updated MS²PIP web server supports cutting-edge proteomics applications
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 a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320101/ https://www.ncbi.nlm.nih.gov/pubmed/37140039 http://dx.doi.org/10.1093/nar/gkad335 |
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author | Declercq, Arthur Bouwmeester, Robbin Chiva, Cristina Sabidó, Eduard Hirschler, Aurélie Carapito, Christine Martens, Lennart Degroeve, Sven Gabriels, Ralf |
author_facet | Declercq, Arthur Bouwmeester, Robbin Chiva, Cristina Sabidó, Eduard Hirschler, Aurélie Carapito, Christine Martens, Lennart Degroeve, Sven Gabriels, Ralf |
author_sort | Declercq, Arthur |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-10320101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103201012023-07-06 Updated MS²PIP web server supports cutting-edge proteomics applications Declercq, Arthur Bouwmeester, Robbin Chiva, Cristina Sabidó, Eduard Hirschler, Aurélie Carapito, Christine Martens, Lennart Degroeve, Sven Gabriels, Ralf Nucleic Acids Res Web Server Issue 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/. Oxford University Press 2023-05-04 /pmc/articles/PMC10320101/ /pubmed/37140039 http://dx.doi.org/10.1093/nar/gkad335 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Web Server Issue Declercq, Arthur Bouwmeester, Robbin Chiva, Cristina Sabidó, Eduard Hirschler, Aurélie Carapito, Christine Martens, Lennart Degroeve, Sven Gabriels, Ralf Updated MS²PIP web server supports cutting-edge proteomics applications |
title | Updated MS²PIP web server supports cutting-edge proteomics applications |
title_full | Updated MS²PIP web server supports cutting-edge proteomics applications |
title_fullStr | Updated MS²PIP web server supports cutting-edge proteomics applications |
title_full_unstemmed | Updated MS²PIP web server supports cutting-edge proteomics applications |
title_short | Updated MS²PIP web server supports cutting-edge proteomics applications |
title_sort | updated ms²pip web server supports cutting-edge proteomics applications |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320101/ https://www.ncbi.nlm.nih.gov/pubmed/37140039 http://dx.doi.org/10.1093/nar/gkad335 |
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