Moreover, the proposed web server is compared with several previously developed phosphorylation prediction tools, such as DISPHOS (9), PredPhospho (11), GPS (12,13), PPSP (4) and KinasePhos 1.0 (5,6). As given in Table 2, the number of kinases, sensitivity and specificity of prediction and the overall predictive performance of these tools are compared. GPS, PPSP, PredPhospho, KinasePhos 1.0 and the proposed methods all support the identification of kinase-specific phosphorylation sites. Although only the kinase groups containing at least 20 experimental phosphorylation sites were selected to evaluate the average predictive performance, the web server of KinasePhos 2.0 provided the predictive models of 60 kinase-specific groups with at least 10 experimental phosphorylation sites. Because the average predictive performance of serine, threonine and tyrosine of GPS and PPSP cannot be obtained, the predictive performance of three representative kinases such as PKA, PKC and CK2 are compared. As given in Table 2, the predictive performances of three representative kinases in KinasePhos 2.0 are comparable with PredPhospho, GPS, PPSP and KinasePhos 1.0. In particular, KinasePhos 2.0 provides the predictive model for phosphohistidine, whose predictive accuracy is
