After evaluating the trained models for identifying kinase-specific phosphorylation sites, the model with the highest predictive accuracy for each data set was selected. Users can submit their uncharacterized protein sequences and select the kinase-specific models for predicting phosphorylated serine, threonine, tyrosine or histidine. Although only 37 kinase groups containing at least 20 experimental phosphorylation sites were used to evaluate the predictive performance, the web server provides 60 predictive models of the kinase-specific groups with at least 10 experimental phosphorylation sites. As depicted in Figure 3, the web server locates the predictive phosphorylation sites and the involved catalytic protein kinases. In order to reveal the characteristics of the phosphorylation sites including the phosphorylated residues and surrounding sequences, the training phosphorylation sites and constructed sequence logos corresponding to each protein kinase are also provided graphically on the web interface. Moreover, users can download the predicted results with tab-delimited format for further analyses. The web server can accurately and efficiently predict the kinase-specific phosphorylation sites in the input protein sequences.
