{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:47:22Z","timestamp":1761061642161,"version":"3.37.3"},"reference-count":48,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T00:00:00Z","timestamp":1650412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Korea government","award":["2019M3E5D3073568"],"award-info":[{"award-number":["2019M3E5D3073568"]}]},{"name":"Institute of Information & communications Technology Planning & Evaluation"},{"name":"Korea government","award":["2020-0-01373"],"award-info":[{"award-number":["2020-0-01373"]}]},{"name":"Artificial Intelligence Graduate School Program","award":["2021-0-02068"],"award-info":[{"award-number":["2021-0-02068"]}]},{"name":"Artificial Intelligence Innovation Hub"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,26]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Tandem mass tag (TMT)-based tandem mass spectrometry (MS\/MS) has become the method of choice for the quantification of post-translational modifications in complex mixtures. Many cancer proteogenomic studies have highlighted the importance of large-scale phosphopeptide quantification coupled with TMT labeling. Herein, we propose a predicted Spectral DataBase (pSDB) search strategy called Deephos that can improve both sensitivity and specificity in identifying MS\/MS spectra of TMT-labeled phosphopeptides.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>With deep learning-based fragment ion prediction, we compiled a pSDB of TMT-labeled phosphopeptides generated from \u223c8000 human phosphoproteins annotated in UniProt. Deep learning could successfully recognize the fragmentation patterns altered by both TMT labeling and phosphorylation. In addition, we discuss the decoy spectra for false discovery rate (FDR) estimation in the pSDB search. We show that FDR could be inaccurately estimated by the existing decoy spectra generation methods and propose an innovative method to generate decoy spectra for more accurate FDR estimation. The utilities of Deephos were demonstrated in multi-stage analyses (coupled with database searches) of glioblastoma, acute myeloid leukemia and breast cancer phosphoproteomes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>Deephos pSDB and the search software are available at https:\/\/github.com\/seungjinna\/deephos.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac280","type":"journal-article","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T11:10:15Z","timestamp":1649934615000},"page":"2980-2987","source":"Crossref","is-referenced-by-count":8,"title":["Deephos: predicted spectral database search for TMT-labeled phosphopeptides and its false discovery rate estimation"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5159-2048","authenticated-orcid":false,"given":"Seungjin","family":"Na","sequence":"first","affiliation":[{"name":"Institute for Artificial Intelligence Research, Hanyang University , Seoul 04763, Republic of Korea"}]},{"given":"Hyunjin","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Automotive Engineering, Hanyang University , Seoul 04763, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3655-9749","authenticated-orcid":false,"given":"Eunok","family":"Paek","sequence":"additional","affiliation":[{"name":"Institute for Artificial Intelligence Research, Hanyang University , Seoul 04763, Republic of Korea"},{"name":"Department of Computer Science, Hanyang University , Seoul 04763, Republic of Korea"}]}],"member":"286","published-online":{"date-parts":[[2022,4,20]]},"reference":[{"key":"2023041403085093700_","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1038\/nature01511","article-title":"Mass spectrometry-based proteomics","volume":"422","author":"Aebersold","year":"2003","journal-title":"Nature"},{"key":"2023041403085093700_","doi-asserted-by":"crossref","first-page":"4085","DOI":"10.1002\/pmic.201000665","article-title":"An improved method for the construction of decoy peptide MS\/MS spectra suitable for the accurate estimation of false discovery rates","volume":"11","author":"Ahrn\u00e9","year":"2011","journal-title":"Proteomics"},{"key":"2023041403085093700_","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1002\/jms.1599","article-title":"Phosphopeptide fragmentation and analysis by mass spectrometry","volume":"44","author":"Boersema","year":"2009","journal-title":"J. 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