Identification of Potential Driver Genes and Pathways Based on Transcriptomics Data in Alzheimer's Disease.
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ABSTRACT:
SUBMITTER: Xia LY
PROVIDER: S-EPMC8985410 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Identification of Potential Driver Genes and Pathways Based on Transcriptomics Data in Alzheimer's Disease.
Xia Liang-Yong LY Tang Lihong L Huang Hui H Luo Jie J
Frontiers in aging neuroscience 20220318
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. To identify AD-related genes from transcriptomics and help to develop new drugs to treat AD. In this study, firstly, we obtained differentially expressed genes (DEG)-enriched coexpression networks between AD and normal samples in multiple transcriptomics datasets by weighted gene co-expression network analysis (WGCNA). Then, a convergent genomic approach (CFG) integrating multiple AD-related evidence was used to prior ...[more]
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