ArticleGlycobiology2025
GlycoSiteMiner: an ML/AI-assisted literature mining-based pipeline for extracting glycosylation sites from PubMed abstracts.
Article in Glycobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- AI in biocuration: challenges, opportunities, and a roadmap for sustainable integration.Bioinformatics advances · 2026Article
- Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome.Journal of cardiovascular development and disease · 2026Review
- Bridging worlds: connecting glycan representations with glycoinformatics via Universal Input and a canonicalized nomenclature.Bioinformatics 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
13 authors.
Funding
Abstract
Over 50% of human proteins are estimated to be glycosylated, making glycosylation one of the most common post-translational modifications (PTMs) of proteins. A glycoinformatics resource such as the GlyGen knowledgebase, consisting of experimentally verified sequence-specific glycosylation sites, is critical for advancing research in glycobiology. Unfortunately, most experimental studies report glycosylation sites in free text format in scientific literature, mentioning gene names and amino acid positions without providing protein sequence identifiers, making it difficult to mine reported sites that can be mapped onto specific protein sequences. We have developed GlycoSiteMiner, which is an automated literature mining-based pipeline that extracts experimentally verified protein sequence-specific glycosylation sites from PubMed abstracts. The pipeline employs ML/AI algorithms to filter out incorrectly identified sites and has been applied to 33 million PubMed abstracts, identifying 1118 new sequence-specific glycosylation sites that were not previously present in the GlyGen resource.
Indexed as
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.