{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T22:28:30Z","timestamp":1793658510176,"version":"4.5.1"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"am","delay-in-days":316,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01-GM-094231"],"award-info":[{"award-number":["R01-GM-094231"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U24-CA271037"],"award-info":[{"award-number":["U24-CA271037"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmn.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Current Opinion in Chemical Biology"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1016\/j.cbpa.2022.102238","type":"journal-article","created":{"date-parts":[[2022,12,14]],"date-time":"2022-12-14T05:56:10Z","timestamp":1670997370000},"page":"102238","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":47,"special_numbering":"C","title":["Recent advances in computational algorithms and software for large-scale glycoproteomics"],"prefix":"10.1016","volume":"72","author":[{"given":"Daniel A.","family":"Polasky","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexey I.","family":"Nesvizhskii","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cbpa.2022.102238_bib1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1093\/glycob\/cww086","article-title":"Biological roles of glycans","volume":"27","author":"Varki","year":"2017","journal-title":"Glycobiology"},{"key":"10.1016\/j.cbpa.2022.102238_bib2","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1074\/mcp.O115.057638","article-title":"Maturing glycoproteomics technologies provide unique structural insights into the N-glycoproteome and its regulation in health and disease","volume":"15","author":"Thaysen-Andersen","year":"2016","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib3","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1038\/s43586-022-00128-4","article-title":"Glycoproteomics","volume":"2","author":"Bagdonaite","year":"2022","journal-title":"Nat Rev Methods Primers"},{"key":"10.1016\/j.cbpa.2022.102238_bib4","doi-asserted-by":"crossref","DOI":"10.1074\/mcp.R120.002277","article-title":"A\u00a0pragmatic guide to enrichment strategies for mass spectrometry-based glycoproteomics","volume":"20","author":"Riley","year":"2021","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib5","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1021\/acs.analchem.9b04651","article-title":"Recent advances in glycoproteomic analysis by mass spectrometry","volume":"92","author":"Suttapitugsakul","year":"2020","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib6","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.sbi.2020.10.028","article-title":"Glycoproteomics: growing up fast","volume":"68","author":"Thomas","year":"2021","journal-title":"Curr Opin Struct Biol"},{"key":"10.1016\/j.cbpa.2022.102238_bib7","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.trac.2018.09.007","article-title":"The benefits of hybrid fragmentation methods for glycoproteomics","volume":"108","author":"Reiding","year":"2018","journal-title":"Trac Trends Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib8","doi-asserted-by":"crossref","first-page":"3286","DOI":"10.1021\/acs.jproteome.0c00218","article-title":"Optimal dissociation methods differ for N- and O-glycopeptides","volume":"19","author":"Riley","year":"2020","journal-title":"J\u00a0Proteome Res"},{"key":"10.1016\/j.cbpa.2022.102238_bib9","doi-asserted-by":"crossref","DOI":"10.1074\/mcp.R120.002090","article-title":"Recent advances in software tools for more generic and precise intact glycopeptide analysis","volume":"20","author":"Cao","year":"2021","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_sref10","article-title":"Byonic: advanced peptide and protein identification software","volume":"13","author":"Bern","year":"2012","journal-title":"Curr Protoc Bioinformatics"},{"key":"10.1016\/j.cbpa.2022.102238_bib11","doi-asserted-by":"crossref","first-page":"2386","DOI":"10.1074\/mcp.M800021-MCP200","article-title":"In-depth analysis of tandem mass spectrometry data from disparate instrument types","volume":"7","author":"Chalkley","year":"2008","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib12","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0045474","article-title":"GlycReSoft: a software package for automated recognition of glycans from LC\/MS data","volume":"7","author":"Maxwell","year":"2012","journal-title":"PLoS One"},{"key":"10.1016\/j.cbpa.2022.102238_bib13","doi-asserted-by":"crossref","DOI":"10.1074\/mcp.RA120.002260","article-title":"Peak filtering, peak annotation, and wildcard search for glycoproteomics","volume":"20","author":"Roushan","year":"2021","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib14","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/s00216-016-9981-2","article-title":"Use of a glycosylation site database to improve glycopeptide identification from complex mixtures","volume":"409","author":"Chalkley","year":"2017","journal-title":"Anal Bioanal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib15","doi-asserted-by":"crossref","first-page":"2466","DOI":"10.1021\/ac5044829","article-title":"MAGIC: an automated N-linked glycoprotein identification tool using a Y1-ion pattern matching algorithm and in silico MS(2) approach","volume":"87","author":"Lynn","year":"2015","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib16","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1038\/s41467-017-00535-2","article-title":"pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification","volume":"8","author":"Liu","year":"2017","journal-title":"Nat Commun"},{"key":"10.1016\/j.cbpa.2022.102238_sref17","doi-asserted-by":"crossref","first-page":"1515","DOI":"10.1038\/s41592-021-01306-0","article-title":"Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3","volume":"18","author":"Zeng","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.cbpa.2022.102238_bib18","doi-asserted-by":"crossref","first-page":"2885","DOI":"10.1021\/acs.jproteome.9b00191","article-title":"GPSeeker enables quantitative structural N-glycoproteomics for site- and structure-specific characterization of differentially expressed N-glycosylation in hepatocellular carcinoma","volume":"18","author":"Xiao","year":"2019","journal-title":"J\u00a0Proteome Res"},{"key":"10.1016\/j.cbpa.2022.102238_sref19","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1038\/s41592-021-01209-0","article-title":"StrucGP: de novo structural sequencing of site-specific N-glycan on glycoproteins using a modularization strategy","volume":"18","author":"Shen","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.cbpa.2022.102238_sref20","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1038\/s41467-022-29530-y","article-title":"Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation","volume":"13","author":"Fang","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.cbpa.2022.102238_sref21","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1038\/s41592-020-0967-9","article-title":"Fast and comprehensive N- and O-glycoproteomics analysis with MSFragger-Glyco","volume":"17","author":"Polasky","year":"2020","journal-title":"Nat Methods"},{"key":"10.1016\/j.cbpa.2022.102238_sref22","doi-asserted-by":"crossref","first-page":"8065","DOI":"10.1021\/acs.analchem.8b01137","article-title":"Reanalysis of global proteomic and phosphoproteomic data identified a large number of glycopeptides","volume":"90","author":"Hu","year":"2018","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_sref23","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.1038\/s41592-020-00985-5","article-title":"O-pair search with MetaMorpheus for O-glycopeptide characterization","volume":"17","author":"Lu","year":"2020","journal-title":"Nat Methods"},{"key":"10.1016\/j.cbpa.2022.102238_bib24","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1038\/nmeth.4256","article-title":"MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics","volume":"14","author":"Kong","year":"2017","journal-title":"Nat Methods"},{"key":"10.1016\/j.cbpa.2022.102238_sref25","doi-asserted-by":"crossref","DOI":"10.1016\/j.mcpro.2022.100205","article-title":"Multiattribute glycan identification and FDR control for glycoproteomics","volume":"21","author":"Polasky","year":"2022","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib26","doi-asserted-by":"crossref","first-page":"14878","DOI":"10.1021\/acs.analchem.0c02950","article-title":"Electron-based dissociation is needed for O-glycopeptides derived from OpeRATOR proteolysis","volume":"92","author":"Riley","year":"2020","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib27","doi-asserted-by":"crossref","first-page":"3852","DOI":"10.1021\/acs.analchem.8b04184","article-title":"A\u00a0new searching strategy for the identification of O-linked glycopeptides","volume":"91","author":"Mao","year":"2019","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib28","doi-asserted-by":"crossref","first-page":"3409","DOI":"10.1074\/mcp.M113.028928","article-title":"LuciPHOr: algorithm for phosphorylation site localization with false localization rate estimation using modified target-decoy approach","volume":"12","author":"Fermin","year":"2013","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib29","doi-asserted-by":"crossref","first-page":"2092","DOI":"10.1016\/j.jprot.2010.08.009","article-title":"A\u00a0survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics","volume":"73","author":"Nesvizhskii","year":"2010","journal-title":"J\u00a0Proteonomics"},{"key":"10.1016\/j.cbpa.2022.102238_sref30","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1038\/s41592-021-01309-x","article-title":"Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis","volume":"18","author":"Kawahara","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.cbpa.2022.102238_bib31","doi-asserted-by":"crossref","first-page":"9212","DOI":"10.1021\/ac502176n","article-title":"New glycoproteomics software, GlycoPep Evaluator, generates decoy glycopeptides de novo and enables accurate false discovery rate analysis for small data sets","volume":"86","author":"Zhu","year":"2014","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib32","doi-asserted-by":"crossref","first-page":"2896","DOI":"10.1021\/acs.jproteome.9b00203","article-title":"DecoyDeveloper: an on-demand, de novo decoy glycopeptide generator","volume":"18","author":"Shipman","year":"2019","journal-title":"J\u00a0Proteome Res"},{"key":"10.1016\/j.cbpa.2022.102238_bib33","article-title":"Integrated GlycoProteome analyzer (I-GPA) for automated identification and quantitation of site-specific N-glycosylation","volume":"6","author":"Park","year":"2016","journal-title":"Sci Rep"},{"key":"10.1016\/j.cbpa.2022.102238_bib34","article-title":"pGlyco: a pipeline for the identification of intact N-glycopeptides by using HCD- and CID-MS\/MS and MS3","volume":"6","author":"Zeng","year":"2016","journal-title":"Sci Rep"},{"key":"10.1016\/j.cbpa.2022.102238_bib35","doi-asserted-by":"crossref","first-page":"2032","DOI":"10.1074\/mcp.M117.068239","article-title":"A\u00a0comprehensive, open-source platform for mass spectrometry-based glycoproteomics data analysis","volume":"16","author":"Liu","year":"2017","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib36","doi-asserted-by":"crossref","first-page":"3511","DOI":"10.1093\/bioinformatics\/bty397","article-title":"Application of network smoothing to glycan LC-MS profiling","volume":"34","author":"Klein","year":"2018","journal-title":"Bioinformatics"},{"key":"10.1016\/j.cbpa.2022.102238_bib37","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1039\/C9MO00178F","article-title":"The effectiveness of filtering glycopeptide peak list files for Y ions","volume":"16","author":"Chalkley","year":"2020","journal-title":"Mol Omics"},{"key":"10.1016\/j.cbpa.2022.102238_bib38","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1074\/mcp.TIR120.002100","article-title":"Open database searching enables the identification and comparison of bacterial glycoproteomes without defining glycan compositions prior to searching","volume":"19","author":"Ahmad Izaham","year":"2020","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib39","doi-asserted-by":"crossref","first-page":"2135","DOI":"10.1002\/1878-0261.13147","article-title":"Precision N-glycoproteomics reveals elevated LacdiNAc as a novel signature of intrahepatic cholangiocarcinoma","volume":"16","author":"Li","year":"2022","journal-title":"Mol Oncol"},{"key":"10.1016\/j.cbpa.2022.102238_bib40","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1002\/mas.20337","article-title":"Mass spectrometric glycan rearrangements","volume":"30","author":"Wuhrer","year":"2011","journal-title":"Mass Spectrom Rev"},{"key":"10.1016\/j.cbpa.2022.102238_bib41","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1093\/glycob\/cwz080","article-title":"GlyGen: computational and informatics resources for glycoscience","volume":"30","author":"York","year":"2020","journal-title":"Glycobiology"},{"key":"10.1016\/j.cbpa.2022.102238_bib42","series-title":"Recent advances in glycoinformatic platforms for glycomics and glycoproteomics","first-page":"56","volume":"62","author":"Abrahams","year":"2020"},{"key":"10.1016\/j.cbpa.2022.102238_bib43","doi-asserted-by":"crossref","first-page":"5330","DOI":"10.1093\/bioinformatics\/btaa1042","article-title":"SugarPy facilitates the universal, discovery-driven analysis of intact glycopeptides","volume":"36","author":"Schulze","year":"2020","journal-title":"Bioinformatics"},{"key":"10.1016\/j.cbpa.2022.102238_bib44","doi-asserted-by":"crossref","DOI":"10.1074\/mcp.R120.002095","article-title":"Recent advances in analytical approaches for glycan and glycopeptide quantitation","volume":"20","author":"Delafield","year":"2021","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_bib45","doi-asserted-by":"crossref","first-page":"5268","DOI":"10.1038\/s41467-020-19052-w","article-title":"A\u00a0streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics","volume":"11","author":"Fang","year":"2020","journal-title":"Nat Commun"},{"key":"10.1016\/j.cbpa.2022.102238_bib46","doi-asserted-by":"crossref","first-page":"7547","DOI":"10.1021\/acs.analchem.0c00014","article-title":"Multiplexed comparative analysis of intact glycopeptides using electron-transfer dissociation and synchronous precursor selection based triple-stage mass spectrometry","volume":"92","author":"Zhu","year":"2020","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib47","doi-asserted-by":"crossref","DOI":"10.1074\/mcp.R120.002204","article-title":"The role of data-independent acquisition for glycoproteomics","volume":"20","author":"Ye","year":"2021","journal-title":"Mol Cell Proteomics"},{"key":"10.1016\/j.cbpa.2022.102238_sref48","doi-asserted-by":"crossref","first-page":"6073","DOI":"10.1038\/s41467-021-26246-3","article-title":"GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control","volume":"12","author":"Yang","year":"2021","journal-title":"Nat Commun"},{"key":"10.1016\/j.cbpa.2022.102238_bib49","doi-asserted-by":"crossref","first-page":"2113","DOI":"10.1021\/acs.jproteome.0c00051","article-title":"Relative retention time estimation improves N-glycopeptide identifications by LC-MS\/MS","volume":"19","author":"Klein","year":"2020","journal-title":"J\u00a0Proteome Res"},{"key":"10.1016\/j.cbpa.2022.102238_bib50","doi-asserted-by":"crossref","first-page":"13360","DOI":"10.1021\/acs.analchem.9b02584","article-title":"Retention time prediction for glycopeptides in reversed-phase chromatography for glycoproteomic applications","volume":"91","author":"Ang","year":"2019","journal-title":"Anal Chem"},{"key":"10.1016\/j.cbpa.2022.102238_bib51","doi-asserted-by":"crossref","first-page":"3345","DOI":"10.1021\/acs.jproteome.1c00245","article-title":"GlycoHybridSeq: automated identification of N-linked glycopeptides using Electron Transfer\/high-energy collision Dissociation (EThcD)","volume":"20","author":"Zhang","year":"2021","journal-title":"J\u00a0Proteome Res"},{"key":"10.1016\/j.cbpa.2022.102238_bib52","doi-asserted-by":"crossref","first-page":"7236","DOI":"10.1021\/acs.analchem.9b00594","article-title":"GlycopeptideGraphMS: improved glycopeptide detection and identification by exploiting graph theoretical patterns in mass and retention time","volume":"91","author":"Choo","year":"2019","journal-title":"Anal Chem"}],"container-title":["Current Opinion in Chemical Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1367593122001235?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1367593122001235?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T02:49:21Z","timestamp":1761274161000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1367593122001235"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2]]},"references-count":52,"alternative-id":["S1367593122001235"],"URL":"https:\/\/doi.org\/10.1016\/j.cbpa.2022.102238","relation":{},"ISSN":["1367-5931"],"issn-type":[{"value":"1367-5931","type":"print"}],"subject":[],"published":{"date-parts":[[2023,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Recent advances in computational algorithms and software for large-scale glycoproteomics","name":"articletitle","label":"Article Title"},{"value":"Current Opinion in Chemical Biology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cbpa.2022.102238","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"102238"}}