{"doi":"10.3390/ijms21186727","title":"Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics","abstract":"<jats:p>Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan–protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.</jats:p>","journal":"International Journal of Molecular Sciences","year":2020,"id":632464,"datarank":0.5375278407684165,"base_score":3.58351893845611,"endowment":3.58351893845611,"self_citation_contribution":0.5375278407684165,"citation_network_contribution":0.0,"self_endowment_contribution":0.5375278407684165,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":35,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1639425,"name":"Zhijue Xu","orcid":null,"position":1,"is_corresponding":false},{"id":1639426,"name":"Xiaokun Hong","orcid":null,"position":2,"is_corresponding":false},{"id":367401,"name":"Yan Zhang","orcid":"0000-0002-6041-4454","position":3,"is_corresponding":false},{"id":1036768,"name":"Xia Zou","orcid":"0000-0002-6251-7713","position":4,"is_corresponding":false},{"id":656421,"name":"Xing Li","orcid":"0000-0003-4908-6848","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics","abstract":"<jats:p>Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan–protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.</jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"32937895","pmcid":"PMC7556027","openalex_id":null,"authors":[],"funders":[{"funder_name":"National Major Science and Technology Projects of China","grant_id":"2018ZX10302205","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"31570796, 31770850 and 81802100","title":null},{"funder_name":"Shanghai Sailing Program","grant_id":"18YF1410500","title":null},{"funder_name":"Shanghai Jiao Tong University Interdiscipline with Medicine Program","grant_id":"YG2017MS63","title":null},{"funder_name":"Fundação para a Ciência e a Tecnologia, I.P.","grant_id":"PTDC/CCI-INF/6762/2020","title":"MS3: New foundations for micro-services and serverless systems"}],"total_grants":5,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"gold","license":"CC BY","oa_locations":[{"url":"https://www.mdpi.com/1422-0067/21/18/6727/pdf","host_type":"publisher"},{"url":"https://www.mdpi.com/1422-0067/21/18/6727/pdf?version=1600082554","host_type":"Unpaywall"},{"url":"https://europepmc.org/articles/PMC7556027","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC7556027?pdf=render","host_type":"Europe_PMC"},{"url":"https://doi.org/10.3390/ijms21186727","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/32937895","host_type":""},{"url":"http://dx.doi.org/10.3390/ijms21186727","host_type":""},{"url":"https://dx.doi.org/10.3390/ijms21186727","host_type":""}],"fields_of_study":["0301 basic medicine","0303 health sciences","03 medical and health sciences"],"mesh_terms":["Animals","Humans","Glycoproteins","Polysaccharides","Proteomics","Computational Biology","Glycosylation","Databases, Factual","Glycomics"],"keywords":["Lectin","Glycoprotein","Glycosylation","Glycan","Glycogene","Glycoinformatics","Proteomics","Databases, Factual","Computational Biology","Review","Polysaccharides","Animals","Humans","Glycomics","Glycoproteins"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. Good health"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"uniprot"},{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T09:49:14.276954Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}