ArticleNucleic acids research2017
Prediction of human miRNA target genes using computationally reconstructed ancestral mammalian sequences.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed, 39 citations in OpenAlex.
- circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data.BioData mining · 2025Article
- Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis.BMC bioinformatics · 2025Article
- PhyloPGM: boosting regulatory function prediction accuracy using evolutionary information.Bioinformatics (Oxford, England) · 2022Article
- miRNAs in Lymphocytic Leukaemias-The miRror of Drug Resistance.International journal of molecular sciences · 2022Review
- Dysregulation of MiR-144-5p/RNF187 Axis Contributes To the Progression of Colorectal Cancer.Journal of translational internal medicine · 2022Article
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- Machine Learning Based Methods and Best Practices of microRNA-Target Prediction and Validation.Advances in experimental medicine and biology · 2022Article
- 6'-O-Galloylpaeoniflorin Exerts Inhibitory Bioactivities in Human Neuroblastoma Cells via Modulating AMPK/miR-489/XIAP Pathway.BioMed research international · 2022Article
- Identification of serum microRNA signatures associated with autism spectrum disorder as promising candidate biomarkers.Heliyon · 2021Article
- Variability in porcine microRNA genes and its association with mRNA expression and lipid phenotypes.Genetics, selection, evolution : GSE · 2021Article
- Article
- MicroRNAs in ascending thoracic aortic aneurysms.Bioscience reports · 2020Observational
- RPmirDIP: Reciprocal Perspective improves miRNA targeting prediction.Scientific reports · 2020Article
- Review
- Autologous Exosome Transfer: A New Personalised Treatment Concept to Prevent Colitis in a Murine Model.Journal of Crohn's & colitis · 2020Article
- Circulatory microRNAs: promising non-invasive prognostic and diagnostic biomarkers for parasitic infections.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2020Review
- 6'-O-galloylpaeoniflorin regulates proliferation and metastasis of non-small cell lung cancer through AMPK/miR-299-5p/ATF2 axis.Respiratory research · 2020Article
- Evolutionary dynamics of microRNA target sites across vertebrate evolution.PLoS genetics · 2020Article
- Review
- miR-26a promotes hepatocellular carcinoma invasion and metastasis by inhibiting PTEN and inhibits cell growth by repressing EZH2.Laboratory investigation; a journal of technical methods and pathology · 2019Article
Corrections and comments
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3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNA) are short single-stranded RNA molecules derived from hairpin-forming precursors that play a crucial role as post-transcriptional regulators in eukaryotes and viruses. In the past years, many microRNA target genes (MTGs) have been identified experimentally. However, because of the high costs of experimental approaches, target genes databases remain incomplete. Although several target prediction programs have been developed in the recent years to identify MTGs in silico, their specificity and sensitivity remain low. Here, we propose a new approach called MirAncesTar, which uses ancestral genome reconstruction to boost the accuracy of existing MTGs prediction tools for human miRNAs. For each miRNA and each putative human target UTR, our algorithm makes uses of existing prediction tools to identify putative target sites in the human UTR, as well as in its mammalian orthologs and inferred ancestral sequences. It then evaluates evidence in support of selective pressure to maintain target site counts (rather than sequences), accounting for the possibility of target site turnover. It finally integrates this measure with several simpler ones using a logistic regression predictor. MirAncesTar improves the accuracy of existing MTG predictors by 26% to 157%. Source code and prediction results for human miRNAs, as well as supporting evolutionary data are available at http://cs.mcgill.ca/∼blanchem/mirancestar.
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