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Article

A heterogeneous graph neural network for candidate gene prediction in endometriosis.

Journal of biomedical informatics - 1 Jun 2026

Soo Zelia, Lin Hua, Wu Mengjia, Guo Kairui, Grosser Mark, Zhang Yi, Lu Jie

Abstract excerpt

OBJECTIVE: Precision medicine applications depend on elucidating the underlying molecular mechanisms of disease. However, many disorders, such as endometriosis, remain poorly characterised genetically due to data scarcity, positive-unlabelled (PU) imbalance, and the heterogeneous structure of biomedical knowledge. This study aims to develop HetBio-CLiP, a novel heterogeneous graph-based contrastive learning (CL)...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 41881288
DOI: 10.1016/j.jbi.2026.105028

Genes

ESR1
GREB1
WNT4

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

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