Related Experiment Video
Updated: Jun 27, 2026

Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples
Published on: May 4, 2012
Prediction of glycosylation sites using random forests
Stephen E Hamby1, Jonathan D Hirst
1School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, UK. pcxsh1@nottingham.ac.uk
Background:
Post translational modifications (PTMs) occur in the vast majority of proteins and are essential for function. Prediction of the sequence location of PTMs enhances the functional characterisation of proteins. Glycosylation is one type of PTM, and is implicated in protein folding, transport and function.
Results:
We use the random forest algorithm and pairwise patterns to predict glycosylation sites. We identify pairwise patterns surrounding glycosylation sites and use an odds ratio to weight their propensity of association with modified residues. Our prediction program, GPP (glycosylation prediction program), predicts glycosylation sites with an accuracy of 90.8% for Ser sites, 92.0% for Thr sites and 92.8% for Asn sites. This is significantly better than current glycosylation predictors. We use the trepan algorithm to extract a set of comprehensible rules from GPP, which provide biological insight into all three major glycosylation types.
Conclusion:
We have created an accurate predictor of glycosylation sites and used this to extract comprehensible rules about the glycosylation process. GPP is available online at http://comp.chem.nottingham.ac.uk/glyco/.
Related Concept Videos
Protein Glycosylation
Glycosylation occurs in...
Oligosaccharide Assembly
Multiple sugar molecules that may or may...
End Point Prediction: Gran Plot
For potentiometric titration, the Gran plot is created by plotting the...
Predicting Reaction Outcomes
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
The...
Protein Folding Quality Check in the RER
