ArticleBioinformation2010
Computational discovery of miR-TF regulatory modules in human genome.
Article in Bioinformation, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Computational inference of co-regulatory modules from transcription factors, MicroRNAs, and their targets using CanMod2.Scientific reports · 2025Article
- Regulatory network involving miRNAs and genes in serous ovarian carcinoma.Oncology letters · 2017Article
- Network of microRNA, transcription factors, target genes and host genes in human mesothelioma.Experimental and therapeutic medicine · 2017Article
- Article
- Network analysis of microRNAs, transcription factors, target genes and host genes in human anaplastic astrocytoma.Experimental and therapeutic medicine · 2016Article
- Network analysis of microRNAs, transcription factors, target genes and host genes in nasopharyngeal carcinoma.Oncology letters · 2016Article
- Construction and analysis of three networks of genes and microRNAs in adenocarcinoma.Oncology letters · 2015Article
- Network analysis of microRNAs and genes in human osteosarcoma.Experimental and therapeutic medicine · 2015Article
- Regulatory networks in retinal ischemia-reperfusion injury.BMC genetics · 2015Article
- Integrative identification of deregulated miRNA/TF-mediated gene regulatory loops and networks in prostate cancer.PloS one · 2014Article
- Inferring microRNA and transcription factor regulatory networks in heterogeneous data.BMC bioinformatics · 2013Article
- miR-27b represses migration of mouse MSCs to burned margins and prolongs wound repair through silencing SDF-1a.PloS one · 2013Article
- Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs.BMC systems biology · 2012Article
- Data analysis and data mining: current issues in biomedical informatics.Methods of information in medicine · 2011Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the post-transcriptional level. They play an important role in several biological processes such as cell development and differentiation. Similar to transcription factors (TFs), miRNAs regulate gene expression in a combinatorial fashion, i.e., an individual miRNA can regulate multiple genes, and an individual gene can be regulated by multiple miRNAs. The functions of TFs in biological regulatory networks have been well explored. And, recently, a few studies have explored miRNA functions in the context of gene regulation networks. However, how TFs and miRNAs function together in the gene regulatory network has not yet been examined. In this paper, we propose a new computational method to discover the gene regulatory modules that consist of miRNAs, TFs, and genes regulated by them. We analyzed the regulatory associations among the sets of predicted miRNAs and sets of TFs on the sets of genes regulated by them in the human genome. We found 182 gene regulatory modules of combinatorial regulation by miRNAs and TFs (miR-TF modules). By validating these modules with the Gene Ontology (GO) and the literature, it was found that our method allows us to detect functionally-correlated gene regulatory modules involved in specific biological processes. Moreover, our miR-TF modules provide a global view of coordinated regulation of target genes by miRNAs and TFs.
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Registered trials
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.