Enhancing link prediction in biomedical knowledge graphs with BioPathNet (opens in new tab)

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Biological entities interact in complex ways, crucial for sustaining life1. Understanding these interactions is central to systems biology, with network analysis playing a key role2. Biological networks are represented as graphs, where nodes can represent genes, proteins, diseases and more, and edges denote associations between them. Edges in a biological graph can signify co-regulation between genes or causal relationship (regulatory network)3,4, physical interactions (in protein–protein interaction networks (PPI)5,6), as well as disease–gene associations (such as in disease–gene networks7,8), among many.

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