Fig. 3: Evidential deep learning provides a favorable measure of uncertainty.
From: Evidential deep learning-based drug-target interaction prediction
a A Mann–Whitney test was performed on the error distribution of uncertainty in samples classified as TP, FP, FN, TN for three datasets: DrugBank (n = 3312 observations), KIBA (n = 11,639 observations), and Davis (n = 2,583 observations). The central line indicates the median, the box bounds indicate the 25th and 75th percentiles, whiskers extend to the minimum and maximum values (within 1.5× interquartile range), and outliers are shown as individual points. All tests were two-sided, with no adjustments made for multiple comparisons. Asterisks indicate statistically significant differences based on Mann–Whitney U test p-values: ****p ≤ 0.0001. Significance is indicated as follows: For DrugBank dataset, TP vs. FN has a p-value of 1.055e-10, FP vs. TN has a p-value of 4.954e-74, TP vs. FP has a p-value of 1.546e-51, FN vs. TN has a p-value of 1.895e-26. For KIBA dataset, TP vs. FN has a p-value of 9.713e-30, FP vs. TN has a p-value of 4.954e-74, TP vs. FP has a p-value of 1.546e-51, FN vs. TN has a p-value of 1.895e-26. For Davis dataset, TP vs. FN has a p-value of 3.502e-09, FP vs. TN has a p-value of 5.662e-45, TP vs. FP has a p-value of 6.667e-21, FN vs. TN has a p-value of 7.434e-40. b Test data sorted and divided into 20 confidence intervals based on uncertainty. All tests were two-sided with no adjustments made for multiple comparisons. The ACC was calculated for samples within each confidence interval. Five independent replications (n = 5) were performed in each data set. Data are presented as mean ± std. Source data for the figure are shown in Supplementary Data. Source data are provided as a Source Data file.
