ArticleBioinformatics advances2025
Bridging worlds: connecting glycan representations with glycoinformatics via Universal Input and a canonicalized nomenclature.
Article in Bioinformatics advances, 2025. 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.
- GlyContact analyzes glycan 3D structures at scale.Nature communications · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: As the field of glycobiology has developed, so too have different glycan nomenclature systems. While each system serves specific purposes, this multiplicity creates challenges for usability, data integration, and knowledge sharing across different databases and computational tools. Results: We present a practical framework for automated nomenclature conversion that takes any glycan nomenclature as input without requiring declaration of the specific language and outputs a canonicalized IUPAC-condensed format as a standardized representation. Our implementation handles all common nomenclatures including WURCS, GlycoCT, IUPAC-condensed/extended, GLYCAM, CSDB-linear, LinearCode, GlycoWorkbench, GlySeeker, Oxford, and KCF, along with common typos, and manages complex cases including structural ambiguities, modifications, uncertainty in linkage information, and different compositional representations. This Universal Input framework can translate more than 10 nomenclatures in <1 ms per glycan, tested on over 150 000 sequences with 98%-100% coverage, enabling seamless integration of existing glycan databases and tools while maintaining the specific advantages of each representation system. Availability and implementation: Universal Input is implemented within the glycowork Python package, available at https://github.com/BojarLab/glycowork and our web app https://canonicalize.streamlit.app/.
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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.