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Table 7 Comparison of virtual screening performance of SVM with those of other methods

From: Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries

Method Inhibitors in training set Inhibitors in testing set Virtual screening performance
No of inhibitors No of chemical families covered by inhibitors No of inhibitors No of chemical families covered by inhibitors Percent of inhibitors in chemical families covered by inhibitors in training set Yield No and Percent of identified true inhibitors outside training chemical families No and Percent of the 168K MDDR compounds identified as inhibitors No and Percent of the 9,305 MDDR compounds similar to the known inhibitors identified as virtual inhibitors
Support Vector Machines 1703 493 44 35 51.43% 70.45% 15(34.1%) 1,496 (0.89%) 719 (7.73%)
Tanimoto Similarity 36.84% 9(20.5%) 9,305 (5.54%) 9,305 (100%)
K Nearest Neighbour 38.64% 10(22.7%) 4,182 (2.49%) 1,169 (12.57%)
Probabilistic Neural Network       50.0% 13(29.5%) 4,386 (2.60%) 1,184 (12.72%)