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Table 14 AUPR, AUC, and CI for different kernels under CVT setting

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

Kernel

Method

AUPR

AUC

CI

CI_PCC

2D

Kronecker_rls

0.5010

0.8912

0.8037

–

DTIP_MDHN

0.7919

0.9701

0.7875

0.8293

3D

Kronecker_rls

0.5494

0.9045

0.8192

–

DTIP_MDHN

0.7903

0.9708

0.7854

0.8344

ECFP4

Kronecker_rls

0.6024

0.9201

0.8408

–

DTIP_MDHN

0.7942

0.9700

0.8313

0.8354

  1. The best results in each column are in bold. CI_PCC is the values of CI calculated by DTIP_MDHN with PCC kernel
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BMC Bioinformatics

ISSN: 1471-2105

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