The role of graph topology in the performance of biomedical Knowledge Graph Completion models.

ABSTRACT:

Motivation

Knowledge Graph Completion has been increasingly adopted as a useful method for helping address several tasks in biomedical research, such as drug repurposing or drug-target identification. To that end, a variety of datasets and Knowledge Graph Embedding models have been proposed over the years. However, little is known about the properties that render a dataset, and associated modelling choices, useful for a given task. Moreover, even though theoretical properties of Knowledge Graph Embedding models are well understood, their practical utility in this field remains controversial.

Results

In this work, we conduct a comprehensive investigation into the topological properties of publicly available biomedical Knowledge Graphs and establish links to the accuracy obser

SUBMITTER: Cattaneo A 

PROVIDER: S-EPMC12560816 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature