ArticlePloS one2014
The CO-Regulation Database (CORD): a tool to identify coordinately expressed genes.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Trial
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- proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms.Nucleic acids research · 2022Article
- Dysregulation of a specific immune-related network of genes biologically defines a subset of schizophrenia.Translational psychiatry · 2019Article
- Deletion of Sulfonylurea Receptor 2 in the Adult Myocardium Enhances Cardiac Glucose Uptake and Is Cardioprotective.JACC. Basic to translational science · 2019Article
- Genome-wide map of proximity linkage to renin proximal promoter in rat.Physiological genomics · 2018Article
- Transcriptome-wide co-expression analysis identifies LRRC2 as a novel mediator of mitochondrial and cardiac function.PloS one · 2017Article
- Downregulation of vimentin in macrophages infected with live Mycobacterium tuberculosis is mediated by Reactive Oxygen Species.Scientific reports · 2016Article
- Pappa2 is linked to salt-sensitive hypertension in Dahl S rats.Physiological genomics · 2016Article
- Article
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Authors and funding
3 authors.
Funding
Abstract
backgroundMeta-analysis of gene expression array databases has the potential to reveal information about gene function. The identification of gene-gene interactions may be inferred from gene expression information but such meta-analysis is often limited to a single microarray platform. To address this limitation, we developed a gene-centered approach to analyze differential expression across thousands of gene expression experiments and created the CO-Regulation Database (CORD) to determine which genes are correlated with a queried gene.
resultsUsing the GEO and ArrayExpress database, we analyzed over 120,000 group by group experiments from gene microarrays to determine the correlating genes for over 30,000 different genes or hypothesized genes. CORD output data is presented for sample queries with focus on genes with well-known interaction networks including p16 (CDKN2A), vimentin (VIM), MyoD (MYOD1). CDKN2A, VIM, and MYOD1 all displayed gene correlations consistent with known interacting genes.
conclusionsWe developed a facile, web-enabled program to determine gene-gene correlations across different gene expression microarray platforms. Using well-characterized genes, we illustrate how CORD's identification of co-expressed genes contributes to a better understanding a gene's potential function. The website is found at http://cord-db.org.
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