Article

MORGaN: self-supervised multi-relational graph learning for drug target discovery

2025-09-16

Abstract excerpt

Identifying therapeutically tractable targets remains difficult, partly because disease biology is distributed across multiple molecular layers and relation types, while labeled data are scarce. We present MORGaN, a self-supervised framework for node classification on multi-omic, multi-relation gene networks that learns structure-aware embeddings and outputs calibrated scores to prioritize therapeutic targets. On...

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Literature Corpus work: 7fb8dd47-c3ee-538e-bbdb-3c06ba356679
DOI: 10.1101/2025.09.10.675402

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