Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Declercq, Arthur, Bouwmeester, Robbin, Chiva, Cristina, Sabidó, Eduard, Hirschler, Aurélie, Carapito, Christine, Martens, Lennart, Degroeve, Sven, Gabriels, Ralf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
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
_version_ 1785068377880920064
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
work_keys_str_mv AT declercqarthur updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT bouwmeesterrobbin updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT chivacristina updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT sabidoeduard updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT hirschleraurelie updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT carapitochristine updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT martenslennart updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT degroevesven updatedms2pipwebserversupportscuttingedgeproteomicsapplications
AT gabrielsralf updatedms2pipwebserversupportscuttingedgeproteomicsapplications