ReviewInternational journal of molecular sciences2020
Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics.
Review in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Orthodox vs. Paradox: Supporting the Central Dogma With Sugar Code.Proteomics · 2026Review
- Metabolic set theory: a generalized model of microbial interactions.NPJ systems biology and applications · 2026Article
- Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort.The Journal of molecular diagnostics : JMD · 2024Article
- Review
- Glycoproteins Involved in Sea Urchin Temporary Adhesion.Marine drugs · 2023Article
- Cysteine Pathogenic Variants of PMM2 Are Sensitive to Environmental Stress with Loss of Structural Stability.Oxidative medicine and cellular longevity · 2023Article
- Quantum computing algorithms: getting closer to critical problems in computational biology.Briefings in bioinformatics · 2022Review
- Artificial intelligence in the analysis of glycosylation data.Biotechnology advances · 2022Review
- Immunoglobulin G N-glycan Biomarkers for Autoimmune Diseases: Current State and a Glycoinformatics Perspective.International journal of molecular sciences · 2022Review
- Source files of the Carbohydrate Structure Database: the way to sophisticated analysis of natural glycans.Scientific data · 2022Article
- The glycosylation in SARS-CoV-2 and its receptor ACE2.Signal transduction and targeted therapy · 2021Review
- Prospects and Challenges of the Study of Anti-Glycan Antibodies and Microbiota for the Monitoring of Gastrointestinal Cancer.International journal of molecular sciences · 2021Review
- Putting the pieces together: mapping the O-glycoproteome.Current opinion in biotechnology · 2021Review
- The Hitchhiker's guide to glycoproteomics.Biochemical Society transactions · 2021Review
- Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy.International journal of molecular sciences · 2020Review
- Three-Dimensional Structures of Carbohydrates and Where to Find Them.International journal of molecular sciences · 2020Review
- Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022.Mass spectrometry reviewsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
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.
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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.