ArticleMethods in molecular biology (Clifton, N.J.)2024
ISOGlyP: O-Glycosylation Site Prediction Using Peptide Sequences and GALNTs.
Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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0 citing papers in PubMed, 3 citations in OpenAlex.
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
Mucin-type O-glycosylation is one of the most common posttranslational modifications of proteins. The abnormal expression of various polypeptide GalNAc-transferases (GALNTs) which initiate and define sites of O-glycosylation is linked to many cancers and other diseases. Many current O-glycosylation prediction programs utilize O-glycoproteomics data obtained without using the transferase isoform(s) responsible for the glycosylation. With 20 different GALNTs in humans, having the ability to predict and interpret O-glycosylation sites in terms of specific GALNT 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 https://ISOGlyP.utep.edu . The code is also available on GitHub ( https://github.com/jonmohl/ISOGlyP ).
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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.