Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships.

For example, the NetWAS 3 framework leverages tissue-specific networks in combination with marginally significant GWAS hits as input for deploying a machine learning model to rank candidate genes.

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