ArticleGenomics, proteomics & bioinformatics2012
Whole miRNome-wide differential co-expression of microRNAs.
Article in Genomics, proteomics & bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed, 22 citations in OpenAlex.
- scLM: Automatic Detection of Consensus Gene Clusters Across Multiple Single-cell Datasets.Genomics, proteomics & bioinformatics · 2021Article
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- Co-Expression Network and Pathway Analyses Reveal Important Modules of miRNAs Regulating Milk Yield and Component Traits.International journal of molecular sciences · 2017Article
- Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysis.Cellular oncology (Dordrecht, Netherlands) · 2017Article
- Noncoding RNAs and neurobehavioral mechanisms in psychiatric disease.Molecular psychiatry · 2015Review
- Mining the bladder cancer-associated genes by an integrated strategy for the construction and analysis of differential co-expression networks.BMC genomics · 2015Article
- Identification of suitable reference genes for hepatic microRNA quantitation.BMC research notes · 2014Article
- Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications.Dialogues in clinical neuroscience · 2014Review
- Clinical advances in molecular biomarkers for cancer diagnosis and therapy.International journal of molecular sciences · 2013Review
- DCGL v2.0: an R package for unveiling differential regulation from differential co-expression.PloS one · 2013Article
- MicroRNAs: mechanisms, functions and progress.Genomics, proteomics & bioinformatics · 2012Article
- miRT: a database of validated transcription start sites of human microRNAs.Genomics, proteomics & bioinformatics · 2012Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Co-regulation of genes has been extensively analyzed, however, rather limited knowledge is available on co-regulations within the miRNome. We investigated differential co-expression of microRNAs (miRNAs) based on miRNome profiles of whole blood from 540 individuals. These include patients suffering from different cancer and non-cancer diseases, and unaffected controls. Using hierarchical clustering, we found 9 significant clusters of co-expressed miRNAs containing 2-36 individual miRNAs. Through analyzing multiple sequencing alignments in the clusters, we found that co-expression of miRNAs is associated with both sequence similarity and genomic co-localization. We calculated correlations for all 371,953 pairs of miRNAs for all 540 individuals and identified 184 pairs of miRNAs with high correlation values. Out of these 184 pairs of miRNAs, 16 pairs (8.7%) were differentially co-expressed in unaffected controls, cancer patients and patients with non-cancer diseases. By computing correlated and anti-correlated miRNA pairs, we constructed a network with 184 putative co-regulations as edges and 100 miRNAs as nodes. Thereby, we detected specific clusters of miRNAs with high and low correlation values. Our approach represents the most comprehensive co-regulation analysis based on whole miRNome-wide expression profiling. Our findings further decrypt the interactions of miRNAs in normal and human pathological processes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.