ReviewClinical proteomics2014
Glycoproteomic and glycomic databases.
Review in Clinical proteomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- A reference dataset of O-GlcNAc proteins in quadriceps skeletal muscle from mice.Glycobiology · 2025Article
- Review
- Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis.International journal of molecular sciences · 2021Review
- FGDB: Database of follicle stimulating hormone glycans.Computational and structural biotechnology journal · 2021Article
- Protein Glycosylation and Tumor Microenvironment Alterations Driving Cancer Hallmarks.Frontiers in oncology · 2019Review
- Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses.Chemical reviews · 2018Review
- Recent Advances in the Mass Spectrometry Methods for Glycomics and Cancer.Analytical chemistry · 2018Review
- Combination of Microwave-Assisted Girard Derivatization with Ionic Liquid Matrix for Sensitive MALDI-TOF MS Analysis of Human Serum N-Glycans.Journal of analytical methods in chemistry · 2018Article
- High-throughput analysis of N-glycans using AutoTip via glycoprotein immobilization.Scientific reports · 2017Article
- Maturing Glycoproteomics Technologies Provide Unique Structural Insights into the N-glycoproteome and Its Regulation in Health and Disease.Molecular & cellular proteomics : MCP · 2016Review
- Coupling enrichment methods with proteomics for understanding and treating disease.Proteomics. Clinical applications · 2015Review
- Direct analysis of hCGβcf glycosylation in normal and aberrant pregnancy by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.International journal of molecular sciences · 2014Article
- Crossroads between Bacterial and Mammalian Glycosyltransferases.Frontiers in immunology · 2014Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.