MSBooster: improving peptide identification rates using deep learning-based features
MSBooster: improving peptide identification rates using deep learning-based features
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additio...
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Full title
MSBooster: improving peptide identification rates using deep learning-based features
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TN_cdi_doaj_primary_oai_doaj_org_article_0dce4b6c30fc4ff787d977d52344de50
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0dce4b6c30fc4ff787d977d52344de50
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ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-023-40129-9
