Drug Repurposing using consilience of Knowledge Graph Completion methods.

ABSTRACT: While link prediction methods in knowledge graphs have been increasingly utilized to locate potential associations between compounds and diseases, they suffer from lack of sufficient evidence to explain why a drug and a disease may be indicated. This is especially true for knowledge graph embedding (KGE) based methods where a drug-disease indication is linked only by information gleaned from a vector representation. Complementary pathwalking algorithms can increase the confidence of drug repurposing candidates by traversing a knowledge graph. However, these methods heavily weigh the relatedness of drugs, through their targets, pharmacology or shared diseases. Furthermore, these methods can rely on arbitrarily extracted paths as evidence of a compound to disease indication and lack the abil

SUBMITTER: Tu R 

PROVIDER: S-EPMC11326126 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature