such as reduced alphabet (3-classes, 7-classes and 8-classes), BLOSUM62 profile encoding and 20-dimensional vector. Because the average predictive performance of the kinase-specific phosphorylation sites with small training set may be overestimated, the SVM models of kinase-specific group whose data size is smaller than 20 training sequences are not considered. Figure 2 gives the average predictive accuracies of models trained with coupling patterns (CP difference or CP ratio) of phosphoserine, phosphothreonine, phosphotyrosine and phosphohistidine are 86, 93, 88 and 93%, respectively. The overall predictive performance of SVM models trained with the features of coupling patterns, whose accuracy is close to 90%, is performing better than the SVM models trained only with sequence profiles (Seq).
