After constructing the drug-target interaction predictor, we have to evaluate its performance. In statistical prediction, the following three cross-validation methods are often used to examine a predictor for its effectiveness in practical application: independent dataset test, subsampling (K-fold cross-validation) test, and jackknife test [92] . However, as elucidated by [24] and demonstrated by Eq.50 in [93] , among the three cross-validation methods, the jackknife test is deemed the most objective that can always yield a unique result for a given benchmark dataset, and hence has been increasingly used and widely recognized by investigators to examine the accuracy of various predictors (see, e.g. [51, 53, 54, 55, 56, 57, 59, 62, 63, 64, 94, 95, 96] ).'' Accordingly, in this study the jackknife cross-validation was adopted to calculate the success prediction rates as well.