A recent study demonstrated that combining genes with nominally significant GWAS P values and tissue-specific networks were powerful in building machine learning classifiers for identifying novel genes associated with disease [ 57 ].
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Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer's disease.
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