Evidence map›Paper›PMID 32681163›Full record

ArticleGlycobiology2021

ISOGlyP: de novo prediction of isoform-specific mucin-type O-glycosylation.

Jonathon E Mohl, Thomas A Gerken, Ming-Ying Leung

Open access · greenAbstract read
In one paragraph

Article in Glycobiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
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

21 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. A Novel Missense Variant ofHuman mutation · 2025
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. ISOGlyP: O-Glycosylation Site Prediction Using Peptide Sequences and GALNTs.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Recombinant mucin biotechnology and engineering.Advanced drug delivery reviews · 2023
    Review
  15. Review
  16. Article
  17. Revealing the human mucinome.Nature communications · 2022
    Article
  18. Article
  19. Article
  20. 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

3 authors at 2 institutions in 1 country.

Jonathon E MohlDepartment of Mathematical Sciences and Border Biomedical Research Center, The University of Texas at El Paso, W University, El Paso, TX 79968, USA.
Thomas A GerkenDepartments of Biochemistry and Chemistry, Case Western Reserve University, Cleveland, OH 44106, USA.
Ming-Ying LeungDepartment of Mathematical Sciences and Border Biomedical Research Center, The University of Texas at El Paso, W University, El Paso, TX 79968, USA.
The University of Texas at El Paso · USCase Western Reserve University · US

Funding

UTEP Border Biomedical Research CenterU54MD007592 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI Yong Qin · 2019 to 2026
$35.1M
Initiation and Regulation of Mucin-Type O-GlycosylationR01GM113534 · NIGMS · CASE WESTERN RESERVE UNIVERSITY · PI GERKEN, THOMAS A · 2018 to 2023
$1.6M
NIGMS NIH HHS R01 GM113534NIMHD NIH HHS U54 MD007592
6 · The paper itself

Abstract

Mucin-type O-glycosylation is one of the most common posttranslational modifications of proteins. The abnormal expression of various polypeptide GalNAc-transferases (GalNAc-Ts) which initiate and define sites of O-glycosylation are linked to many cancers and other diseases. Current O-glycosyation prediction programs utilize O-glycoproteomics data obtained without regard to the transferase isoform (s) responsible for the glycosylation. With 20 different GalNAc-Ts in humans, having an ability to predict and interpret O-glycosylation sites in terms of specific GalNAc-T isoforms is invaluable. To fill this gap, ISOGlyP (Isoform-Specific O-Glycosylation Prediction) has been developed. Using position-specific enhancement values generated based on GalNAc-T isoform-specific amino acid preferences, ISOGlyP predicts the propensity that a site would be glycosylated by a specific transferase. ISOGlyP gave an overall prediction accuracy of 70% against in vivo data, which is comparable to that of the NetOGlyc4.0 predictor. Additionally, ISOGlyP can identify the known effects of long- and short-range prior glycosylation and can generate potential peptide sequences selectively glycosylated by specific isoforms. ISOGlyP is freely available for use at ISOGlyP.utep.edu. The code is also available on GitHub (https://github.com/jonmohl/ISOGlyP).

Indexed as

GlycosylationHumansMucin-1Protein IsoformsMUC1 protein, humanMucin-1Protein IsoformsGalNAc-TGALNTmucin-type O-glycosylationO-glycosylation predictionPTM prediction

Identifiers

PMID32681163
PMCPMC8022967
OpenAlexW3042824191

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.