NetPhosYeast: Prediction of protein phosphorylation sites in yeast.
Christian Ravnsborg Ingrell1,
Martin Lee Miller2,
Ole Nørregaard Jensen1 and
Accepted for publication in Bioinformatics, 2007.
1University of Southern Denmark,
Campusvej 55, DK-5230, Odense M, Denmark
2Center for Biological Sequence Analysis, BioCentrum-DTU,
The Technical University of Denmark, DK-2800 Lyngby, Denmark
We here present a neural network based method for the prediction of
protein phosphorylation sites in yeast - an important model organism
for basic research. Existing protein phosphorylation site predictors
are primarily based on mammalian data and show reduced sensitivity on
yeast phosphorylation sites compared to those in humans, suggesting
the need for a yeast-specific phosphorylation site predictor.
NetPhosYeast achieves a correlation coefficient close to 0.75 with a
sensitivity of 0.84 and specificity of 0.90 and outperforms existing
predictors in the identification of phosphorylation sites in yeast.