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Table 8 AUC and AUPR for DNILMF and DTIP_MDHN on new dataset1 under CVP setting

From: Drug-target interactions prediction using marginalized denoising model on heterogeneous networks

Dataset Method AUPR AUC
Enzymea DNILMF 0.9245 0.9950
DTIP_MDHN 0.9071 0.9911
Ion Channel (IC) DNILMF 0.9921 0.9991
DTIP_MDHN 0.9968 0.9998
GPCR DNILMF 0.9239 0.9935
DTIP_MDHN 0.9615 0.9963
Nuclear Receptor (NR) DNILMF 0.9341 0.9897
DTIP_MDHN 0.9610 0.9910
protein kinase DNILMF 0.8713 0.9875
DTIP_MDHN 0.9408 0.9959
transporter DNILMF 0.8852 0.9907
DTIP_MDHN 0.9523 0.9978
cytokine and cytokine receptor DNILMF 0.8166 0.9827
DTIP_MDHN 0.8630 0.9842
cell surface molecule and ligand DNILMF 0.8557 0.9817
DTIP_MDHN 0.9076 0.9887
ALLa DNILMF 0.7578 0.9813
DTIP_MDHN 0.9743 0.9978
  1. aoptimized parameters (numLatent = 90, c = 20, thisAlpha = 0.7, λu = 10, λv = 10, K = 2) were used in DNILMF