The models trained with various features, including sequence profiles and coupling patterns, were evaluated by 5-fold and Jackknife cross-validation, the predictive performance of the models trained with coupling patterns are better than the models trained with sequence profiles. In general, the previous works of phosphorylation site prediction focused on residues serine, threonine and tyrosine; like our previous work (KinasePhos 1.0). Herein, KinasePhos 2.0 first considers phosphohistidine from Phospho.ELM and Swiss-Prot, which contain one and 42 phosphorylated histidine, respectively.
