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Table 5 Performance of LRSSL and SCMFDD on Liang Dataset

From: Predicting drug-disease associations by using similarity constrained matrix factorization

Methods

AUPR

AUC

SN

SP

ACC

F

LRSSL

0.1789

0.8250

0.2167

0.9989

0.9979

0.2018

SCMFDD-Che-Sem

0.2518

0.9020

0.2799

0.9993

0.9985

0.3030

SCMFDD-Dom-Sem

0.2673

0.9228

0.2851

0.9993

0.9985

0.3088

SCMFDD-Go-Sem

0.2585

0.9210

0.2897

0.9993

0.9985

0.3137

  1. For drugs, Che Chemical Similarity, Dom Protein Domains Similarity, Go Gene ontology Similarity. For diseases, Sem: Semantic Similarity
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BMC Bioinformatics

ISSN: 1471-2105

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