ArticleCells2022
Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome.
Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identification of Endometriosis Pathophysiologic-Related Genes Based on Meta-Analysis and Bayesian Approach.International journal of molecular sciences · 2025Pooled it
- Cardioplegic Machine Perfusion of Hearts Donated after Circulatory Death.Journal of cardiovascular translational research · 2025Article
- Urinary albumin creatinine ratio is associated with lipid profile.Scientific reports · 2024Article
- Article
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Authors and funding
7 authors.
Funding
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Abstract
Inference of co-expression network and identification of disease-related modules and gene sets can help us understand disease-related molecular pathophysiology. We aimed to identify a cardiovascular disease (CVD)-related transcriptomic signature, specifically, in peripheral blood tissue, based on differential expression (DE) and differential co-expression (DcoE) analyses. Publicly available blood sample datasets for coronary artery disease (CAD) and acute coronary syndrome (ACS) statuses were integrated to establish a co-expression network. A weighted gene co-expression network analysis was used to construct modules that include genes with highly correlated expression values. The DE criterion is a linear regression with module eigengenes for module-specific genes calculated from principal component analysis and disease status as the dependent and independent variables, respectively. The DcoE criterion is a paired
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