ROC curve analysis was performed for all the 44 EHPs to evaluate the accuracy of the in silico tools used for functional prediction and domain analysis . For each one out of seven tools, five levels were considered to estimate efficiency. The input data had two columns. The first column was assigned by binary 0 as for true negative prediction and binary 1 for true positive prediction. In the second column, integer values ranging from one to five were assigned, where a higher value indicated higher confidence. The input data was submitted to the ROC Analysis server () following the format 1. Upon executing the online ROC program, the measures of the ROC curve, such as accuracy, sensitivity, specificity, and area under the curve (AUC) were obtained.