Evidence map›Paper›PMID 39720162›Full record

ArticleBBA advances2024

MicroGlycoDB: A database of microbial glycans using Semantic Web technologies.

Sunmyoung Lee, Louis-David Leclercq, Yann Guerardel, Christine M Szymanski, Thomas Hurtaux, Tamara L Doering, Takane Katayama, Kiyotaka Fujita, Kazuhiro Aoki, Kiyoko F Aoki-Kinoshita

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sunmyoung LeeGlycan and Life Systems Integration Center (GaLSIC), Soka University, Hachioji, Tokyo, Japan.
Louis-David LeclercqFrench National Center for Scientific Research (CNRS), University of Lille, Lille, France.
Yann GuerardelFrench National Center for Scientific Research (CNRS), University of Lille, Lille, France.
Christine M SzymanskiComplex Carbohydrate Research Center (CCRC), University of Georgia, Athens, GA, USA.
Thomas HurtauxDepartment of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA.
Tamara L DoeringDepartment of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA.
Takane KatayamaGraduate School of Biostudies, Kyoto University, Kyoto, Japan.
Kiyotaka FujitaThe United Graduate School of Agricultural Sciences, Kagoshima University, Kagoshima, Japan.
Kazuhiro AokiDepartment of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.
Kiyoko F Aoki-KinoshitaGlycan and Life Systems Integration Center (GaLSIC), Soka University, Hachioji, Tokyo, Japan.

Funding

CRYPTOCOCCAL GLYCAN SYNTHESISR01AI135012 · NIAID · WASHINGTON UNIVERSITY · PI DOERING, TAMARA L · 2018 to 2022
$2.5M
NIAID NIH HHS R01 AI135012
6 · The paper itself

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.

Indexed as

DatabaseData integrationGlycosylationMicrobesSemantic data

Identifiers

PMID39720162
PMCPMC11667048

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.