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Table 12 AUPR, AUC, and CI for different kernels under CVP setting

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

Kernel

Method

AUPR

AUC

CI

CI_PCC

2D

Kronecker_rls

0.6586

0.9388

0.8740

–

DTIP_MDHN

0.7706

0.9471

0.8623

0.8740

3D

Kronecker_rls

0.6642

0.9419

0.8778

–

DTIP_MDHN

0.7712

0.9474

0.8821

0.8919

ECFP4

Kronecker_rls

0.6654

0.9444

0.8793

–

DTIP_MDHN

0.7654

0.9457

0.8856

0.9020

  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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