{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T10:33:46Z","timestamp":1793356426072,"version":"4.5.0"},"reference-count":31,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Chromatography B"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.jchromb.2026.125305","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T06:51:18Z","timestamp":1790232678000},"page":"125305","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["GAG-Former: An LC-MS\/MS data-processing workflow with a physics-informed dual-stream transformer backbone for co-elution deconvolution and simultaneous structural identification of glycosaminoglycan disaccharides in biological samples"],"prefix":"10.1016","volume":"1284","author":[{"given":"Chunhua","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anran","family":"Sheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runbo","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojun","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"36","key":"10.1016\/j.jchromb.2026.125305_bb0005","article-title":"Ion mobility mass spectrometry-based disaccharide analysis of glycosaminoglycans","volume":"30","author":"Polewski","year":"2024","journal-title":"Chem. Eur. J."},{"issue":"27","key":"10.1016\/j.jchromb.2026.125305_bb0010","doi-asserted-by":"crossref","first-page":"10087","DOI":"10.1021\/acs.analchem.3c01531","article-title":"Fingerprinting of underivatized monosaccharide stereoisomers using high-resolution ion mobility spectrometry and its implications for carbohydrate sequencing","volume":"95","author":"Ollivier","year":"2023","journal-title":"Anal. Chem."},{"key":"10.1016\/j.jchromb.2026.125305_bb0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.trac.2024.117721","article-title":"Ion mobility mass spectrometry for Glycomics: challenges and opportunities when met with artificial intelligence","volume":"176","author":"Zhu","year":"2024","journal-title":"TrAC Trends Anal. Chem."},{"issue":"32","key":"10.1016\/j.jchromb.2026.125305_bb0020","doi-asserted-by":"crossref","first-page":"17490","DOI":"10.1021\/acs.analchem.5c02338","article-title":"Quantitative HILIC-Q-TOF-MS analysis of glycosaminoglycans and non-reducing end carbohydrate biomarkers via glycan reductive isotopic labeling","volume":"97","author":"Basu","year":"2025","journal-title":"Anal. Chem."},{"key":"10.1016\/j.jchromb.2026.125305_bb0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpba.2024.116625","article-title":"State-of-the-art chromatographic and mass spectrometric techniques in heparin structural analysis","volume":"255","author":"Ouyang","year":"2025","journal-title":"J. Pharm. Biomed. Anal."},{"issue":"12","key":"10.1016\/j.jchromb.2026.125305_bb0030","article-title":"Structural domain analysis of heparin and heparan sulfate combined with label-free quantitative proteomics to elucidate their functional diversity in liver cancer and APAP-induced liver injury","volume":"24","author":"An","year":"2025","journal-title":"Mol. Cell. Proteomics"},{"issue":"7","key":"10.1016\/j.jchromb.2026.125305_bb0035","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.1038\/s41592-024-02314-6","article-title":"Predicting glycan structure from tandem mass spectrometry via deep learning","volume":"21","author":"Urban","year":"2024","journal-title":"Nat. Methods"},{"issue":"5","key":"10.1016\/j.jchromb.2026.125305_bb0040","doi-asserted-by":"crossref","first-page":"2698","DOI":"10.1021\/acs.analchem.4c04531","article-title":"QuanFormer: a transformer-based precise peak detection and quantification tool in LC-MS-based metabolomics","volume":"97","author":"Zhang","year":"2025","journal-title":"Anal. Chem."},{"key":"10.1016\/j.jchromb.2026.125305_bb0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.carbpol.2024.122216","article-title":"Quality control, safety assessment and preparation approaches of low molecular weight heparin","volume":"339","author":"Yu","year":"2024","journal-title":"Carbohydr. Polym."},{"key":"10.1016\/j.jchromb.2026.125305_bb0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.chroma.2024.465482","article-title":"Fingerprinting analyses of low molecular weight heparin with an orthogonal MHC 2D LC-MS system","volume":"1738","author":"Zhang","year":"2024","journal-title":"J. Chromatogr. A"},{"issue":"4","key":"10.1016\/j.jchromb.2026.125305_bb0055","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1039\/D3AY01578E","article-title":"Disaccharide compositional analysis of chondroitin sulphate using WAX HILIC-MS with pre-column procainamide labelling; application to the placenta in pre-eclampsia","volume":"16","author":"Antia","year":"2024","journal-title":"Anal. Methods"},{"key":"10.1016\/j.jchromb.2026.125305_bb0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijbiomac.2024.135833","article-title":"Immobilized high-performance heparin lyase III for efficient preparation of low molecular weight heparin","volume":"280","author":"Yang","year":"2024","journal-title":"Int. J. Biol. Macromol."},{"issue":"1","key":"10.1016\/j.jchromb.2026.125305_bb0065","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s11274-024-04225-2","article-title":"Cloning, expression, and characterization of a heparinase III coupled with heparinase I for enzymatic depolymerization of heparin","volume":"41","author":"Li","year":"2025","journal-title":"World J. Microbiol. Biotechnol."},{"issue":"6","key":"10.1016\/j.jchromb.2026.125305_bb0070","doi-asserted-by":"crossref","first-page":"3045","DOI":"10.1021\/acs.jafc.3c07197","article-title":"Heparinase III with high activity and stability: heterologous expression, biochemical characterization, and application in depolymerization of heparin","volume":"72","author":"Xu","year":"2024","journal-title":"J. Agric. Food Chem."},{"issue":"1","key":"10.1016\/j.jchromb.2026.125305_bb0075","doi-asserted-by":"crossref","first-page":"1326","DOI":"10.1038\/s41467-024-45419-4","article-title":"Structural and mechanistic characterization of bifunctional heparan sulfate N-deacetylase-N-sulfotransferase 1","volume":"15","author":"Mycroft-West","year":"2024","journal-title":"Nat. Commun."},{"issue":"25","key":"10.1016\/j.jchromb.2026.125305_bb0080","doi-asserted-by":"crossref","first-page":"9397","DOI":"10.1021\/acs.analchem.3c00764","article-title":"PeakDetective: a Semisupervised deep learning-based approach for peak curation in untargeted metabolomics","volume":"95","author":"Stancliffe","year":"2023","journal-title":"Anal. Chem."},{"issue":"3","key":"10.1016\/j.jchromb.2026.125305_bb0085","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btae084","article-title":"RT-transformer: retention time prediction for metabolite annotation to assist in metabolite identification","volume":"40","author":"Xue","year":"2024","journal-title":"Bioinformatics"},{"issue":"1","key":"10.1016\/j.jchromb.2026.125305_bb0090","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1186\/s13321-024-00905-1","article-title":"Insights into predicting small molecule retention times in liquid chromatography using deep learning","volume":"16","author":"Liu","year":"2024","journal-title":"J. Cheminform."},{"issue":"8","key":"10.1016\/j.jchromb.2026.125305_bb0095","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1038\/s42256-024-00875-x","article-title":"Deep learning prediction of glycopeptide tandem mass spectra powers glycoproteomics","volume":"6","author":"Zong","year":"2024","journal-title":"Nature Machine Intelligence"},{"issue":"4","key":"10.1016\/j.jchromb.2026.125305_bb0100","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1038\/s42256-024-00816-8","article-title":"Tandem mass spectrum prediction for small molecules using graph transformers","volume":"6","author":"Young","year":"2024","journal-title":"Nature Machine Intelligence"},{"issue":"7","key":"10.1016\/j.jchromb.2026.125305_bb0105","doi-asserted-by":"crossref","first-page":"3722","DOI":"10.1021\/acs.jproteome.5c00063","article-title":"Pairwise attention: leveraging mass differences to enhance de novo sequencing of mass spectra","volume":"24","author":"Lapin","year":"2025","journal-title":"J. Proteome Res."},{"issue":"2","key":"10.1016\/j.jchromb.2026.125305_bb0110","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1021\/acs.jproteome.3c00729","article-title":"AttnPep: a self-attention-based deep learning method for peptide identification in shotgun proteomics","volume":"23","author":"Li","year":"2024","journal-title":"J. Proteome Res."},{"key":"10.1016\/j.jchromb.2026.125305_bb0115","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.3762\/bjoc.19.134","article-title":"GlAIcomics: a deep neural network classifier for spectroscopy-augmented mass spectrometric glycans data","volume":"19","author":"Barillot","year":"2023","journal-title":"Beilstein J. Org. Chem."},{"issue":"51","key":"10.1016\/j.jchromb.2026.125305_bb0120","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adp6040","article-title":"Domain adaptation in small-scale and heterogeneous biological datasets","volume":"10","author":"Orouji","year":"2024","journal-title":"Sci. Adv."},{"issue":"12","key":"10.1016\/j.jchromb.2026.125305_bb0125","doi-asserted-by":"crossref","DOI":"10.1128\/jcm.01186-25","article-title":"Prediction of antimicrobial resistance from MALDI-TOF mass spectra using machine learning: a validation study","volume":"63","author":"Wiesmann","year":"2025","journal-title":"J. Clin. Microbiol."},{"issue":"12","key":"10.1016\/j.jchromb.2026.125305_bb0130","doi-asserted-by":"crossref","first-page":"9023","DOI":"10.1002\/mp.17423","article-title":"Adaptive wavelet-VNet for single-sample test-time adaptation in medical image segmentation","volume":"51","author":"Qian","year":"2024","journal-title":"Med. Phys."},{"key":"10.1016\/j.jchromb.2026.125305_bb0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.trac.2024.117988","article-title":"Machine learning-assisted identification of environmental pollutants by liquid chromatography coupled with high-resolution mass spectrometry","volume":"180","author":"Wang","year":"2024","journal-title":"TrAC Trends Anal. Chem."},{"issue":"4","key":"10.1016\/j.jchromb.2026.125305_bb0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymgme.2024.108535","article-title":"Community consensus for heparan sulfate as a biomarker to support accelerated approval in neuronopathic mucopolysaccharidoses","volume":"142","author":"Muenzer","year":"2024","journal-title":"Mol. Genet. Metab."},{"issue":"Pt A","key":"10.1016\/j.jchromb.2026.125305_bb0145","article-title":"Evaluation of the protective effects of chondroitin sulfate oligosaccharide against osteoarthritis via inactivation of NLRP3 inflammasome by in vivo and in vitro studies","volume":"142","author":"Chang","year":"2024","journal-title":"Int. Immunopharmacol."},{"issue":"8","key":"10.1016\/j.jchromb.2026.125305_bb0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.mcpro.2024.100803","article-title":"Comprehensive glycomic and proteomic analysis of mouse striatum and lateral hypothalamus following repeated exposures to cocaine or methamphetamine","volume":"23","author":"Sethi","year":"2024","journal-title":"Mol. Cell. Proteomics"},{"issue":"22","key":"10.1016\/j.jchromb.2026.125305_bb0155","doi-asserted-by":"crossref","DOI":"10.1172\/JCI195268","article-title":"Reduced heparan sulfate levels in cerebrospinal fluid reflect brain neuron correction in Sanfilippo B mice","volume":"135","author":"Le","year":"2025","journal-title":"J. Clin. Investig."}],"container-title":["Journal of Chromatography B"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1570023226003946?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1570023226003946?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T09:34:52Z","timestamp":1793352892000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1570023226003946"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":31,"alternative-id":["S1570023226003946"],"URL":"https:\/\/doi.org\/10.1016\/j.jchromb.2026.125305","relation":{},"ISSN":["1570-0232"],"issn-type":[{"value":"1570-0232","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"GAG-Former: An LC-MS\/MS data-processing workflow with a physics-informed dual-stream transformer backbone for co-elution deconvolution and simultaneous structural identification of glycosaminoglycan disaccharides in biological samples","name":"articletitle","label":"Article Title"},{"value":"Journal of Chromatography B","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jchromb.2026.125305","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"125305"}}