O-GlcNAcPRED statistics

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Citations per year

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Associated diseases

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O-GlcNAcPRED specifications


Unique identifier OMICS_26961
Alternative name O-GlcNAcPRED-II
Interface Web user interface
Restrictions to use None
Input format FASTA
Computer skills Basic
Stability Stable
Maintained Yes


  • person_outline Cangzhi Jia <>

Publications for O-GlcNAcPRED

O-GlcNAcPRED in publications

PMCID: 5410141
PMID: 28462053
DOI: 10.7717/peerj.3261

[…] bioinformatics tools to identify other ptm sites. developed a prediction tool termed yinoyang which was trained using the local sequences of 40 o-glcnacylation sites. later, a svm-based model named o-glcnacpred was developed for capturing potential o-glcnacylation sites (). meanwhile, provided the online service and local package of gps-yno2 1.0 for identification of tyrosine nitration […]

PMCID: 4682369
PMID: 26680539
DOI: 10.1186/1471-2105-16-S18-S10

[…] in experimentally identified o-glcnacylation sites motivates new developments including oglcnacscan, which was trained using 373 o-glcnacylation sites []. more recently, a new prediction tool, o-glcnacpred, has been proposed claiming to have better performance than the aforementioned tools []. in the midst of these developments, carage et al. have demonstrated that ensembles of support […]

PMCID: 4290634
PMID: 25521204
DOI: 10.1186/1471-2105-15-S16-S1

[…] a prediction program termed yinoyang that was trained with 40 o-glcnaccylation sites []. in 2011, wang et al. have developed oglcnacscan that was trained with 373 o-glcnacylation sites []. in 2013, o-glcnacpred has been proposed and claimed to have better performance than these two aforementioned predictors []., although several methods have been proposed for the computational identification […]

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O-GlcNAcPRED institution(s)
Department of Mathematics, Dalian Maritime University, Dalian, China; School of Computer Science and Technology, Tianjin University, China
O-GlcNAcPRED funding source(s)
Supported by the Fundamental Research Funds for the Central Universities (number 3132016306, 3132017048 and 3132017085); The National Social Science Foundation of China (Grant No.15CGL031); and the Program for Dalian High Level Talent Innovation Support (Grant No.2015R063).

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