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The application of weighted gene co-expression network analysis in identifying key modules and hub genes associated with disease status in Alzheimer’s disease

1 Dec 2019

Abstract excerpt

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative condition that affects more than 15 million individuals globally. However, a predictive molecular biomarker to distinguish the different stages of AD patients is still lacking. METHODS: A weighted gene co-expression network analysis (WGCNA) was employed to systematically identify the co-expressed gene modules and hub genes connected with AD...

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PMID: 32042816
DOI: 10.21037/atm.2019.12.59

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