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Table 1 Median of WAFs with alternative methodologies and with evoKGsim for the different PPI datasets

From: Evolving knowledge graph similarity for supervised learning in complex biomedical domains

Dataset SSM Single and static combinations Exhaustive search Decision evoKGsim
(#interactions)   BP CC MF Avg Max Combinations Trees  
STRING-EC SimGIC 0.648 0.822 0.670 0.825 0.814 0.825 0.804 0.826
(2245) ResnikMax 0.670 0.819 0.641 0.806 0.826 0.817 0.884 0.864
  ResnikBMA 0.661 0.828 0.642 0.831 0.848 0.832 0.837 0.849
STRING-DM SimGIC 0.891 0.880 0.791 0.890 0.891 0.927 0.855 0.936
(550) ResnikMax 0.910 0.899 0.799 0.927 0.927 0.936 0.917 0.937
  ResnikBMA 0.928 0.871 0.794 0.936 0.918 0.963 0.927 0.945
BIND-SC SimGIC 0.849 0.831 0.715 0.854 0.840 0.868 0.830 0.876
(1366) ResnikMax 0.883 0.845 0.775 0.904 0.908 0.923 0.890 0.923
  ResnikBMA 0.864 0.842 0.754 0.901 0.868 0.908 0.872 0.901
DIP/MIPS-SC SimGIC 0.811 0.776 0.690 0.803 0.779 0.818 0.754 0.825
(13807) ResnikMax 0.845 0.798 0.703 0.835 0.838 0.854 0.840 0.849
  ResnikBMA 0.820 0.788 0.698 0.835 0.822 0.842 0.780 0.843
STRING-SC SimGIC 0.802 0.764 0.684 0.804 0.780 0.814 0.766 0.817
(30384) ResnikMax 0.825 0.788 0.682 0.834 0.826 0.839 0.843 0.843
  ResnikBMA 0.818 0.784 0.678 0.837 0.817 0.837 0.793 0.838
DIP-HS SimGIC 0.840 0.746 0.698 0.823 0.768 0.857 0.799 0.861
(2739) ResnikMax 0.892 0.829 0.770 0.885 0.867 0.914 0.894 0.894
  ResnikBMA 0.874 0.773 0.754 0.876 0.811 0.872 0.867 0.881
STRING-HS SimGIC 0.824 0.769 0.700 0.813 0.786 0.823 0.774 0.830
(6912) ResnikMax 0.848 0.763 0.723 0.850 0.811 0.868 0.850 0.867
  ResnikBMA 0.851 0.792 0.725 0.861 0.815 0.870 0.816 0.876
GRID/HPRD-unbal-HS SimGIC 0.686 0.652 0.621 0.685 0.664 0.701 0.621 0.694
(31320) ResnikMax 0.718 0.674 0.655 0.729 0.702 0.734 0.703 0.734
  ResnikBMA 0.717 0.678 0.646 0.737 0.697 0.742 0.662 0.742
GRID/HPRD-bal-HS SimGIC 0.647 0.630 0.618 0.672 0.647 0.674 0.590 0.673
(31349) ResnikMax 0.656 0.602 0.590 0.648 0.636 0.664 0.636 0.654
  ResnikBMA 0.652 0.640 0.597 0.673 0.659 0.674 0.604 0.677
  1. In bold, the best result for each dataset-SSM pair. The median WAF achieved for each baseline is underlined when evoKGsim significantly outperforms the baseline (using α=0.01)