ArticleBBA advances2024
MicroGlycoDB: A database of microbial glycans using Semantic Web technologies.
Article in BBA advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Introduction to a special issue, "Expanded glycomics: A bridge over future glycomics".BBA advances · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Glycoconjugates are present on microbial surfaces and play critical roles in modulating interactions with the environment and the host. Extensive research on microbial glycans, including elucidating the structural diversity of the glycan moieties of glycoconjugates and polysaccharides, has been carried out to investigate the function of glycans in modulating the interactions between the host and microbes, to explore their potential applications in the therapeutic targeting of pathogenic species, and in the use as probiotics in gut microbiomes. However, glycan-related information is dispersed across numerous databases and a vast amount of literature, which makes it laborious and time-consuming to identify and gather the relevant information about microbial glycosylation. This challenge can be addressed by a comprehensive database, which could offer insight into the fundamental processes underlying glycosylation. We have developed a MicroGlycoDB database to provide integrated glycan information on important model microorganisms. The data is described using Semantic Web Technologies, which allow microbial glycan data to be represented in a structured format accessible by machines, thus facilitating data sharing and integration with other resources that catalog features such as pathways, diseases, or interactions. This semantic data based on ontologies will contribute to the discovery of new knowledge in the field of microbiology, along with the expansion of information on the glycosylation of other microorganisms.
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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.