ArticleRNA (New York, N.Y.)2011
MicroRNA transfection and AGO-bound CLIP-seq data sets reveal distinct determinants of miRNA action.
Article in RNA (New York, N.Y.), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 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.
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
45 citing papers in PubMed, 72 citations in OpenAlex.
- Progress and challenges in profiling protein-RNA and protein-associated RNA-RNA interactions.RNA (New York, N.Y.) · 2026Review
- Epitranscriptomic sculpting: the role of mMedical oncology (Northwood, London, England) · 2025Review
- Recent advances in investigation of circRNA/lncRNA-miRNA-mRNA networks through RNA sequencing data analysis.Briefings in functional genomics · 2025Review
- Advanced computational predictive models of miRNA-mRNA interaction efficiency.Computational and structural biotechnology journal · 2024Article
- Determinants of Functional MicroRNA Targeting.Molecules and cells · 2023Review
- miRNA/mRNA co-profiling identifies the miR-200 family as a central regulator of SMC quiescence.iScience · 2022Article
- Machine Learning Based Methods and Best Practices of microRNA-Target Prediction and Validation.Advances in experimental medicine and biology · 2022Article
- miRNA Combinatorics and its Role in Cell State Control-A Probabilistic Approach.Frontiers in molecular biosciences · 2021Article
- A Rapid Evolving microRNA Cluster Rewires Its Target Regulatory Networks inFrontiers in genetics · 2021Article
- A cell-based probabilistic approach unveils the concerted action of miRNAs.PLoS computational biology · 2019Article
- Trends in the development of miRNA bioinformatics tools.Briefings in bioinformatics · 2019Review
- Genome-wide identification of microRNAs regulating the human prion protein.Brain pathology (Zurich, Switzerland) · 2019Article
- Antitumor effect of a new nano-vector with miRNA-135a on malignant glioma.International journal of nanomedicine · 2018Article
- Highly accessible AU-rich regions in 3' untranslated regions are hotspots for binding of regulatory factors.PLoS computational biology · 2017Article
- Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements.Cell reports · 2016Article
- Gene regulation by dietary microRNAs.Canadian journal of physiology and pharmacology · 2015Review
- GDNF Overexpression from the Native Locus Reveals its Role in the Nigrostriatal Dopaminergic System Function.PLoS genetics · 2015Article
- Article
- Transcriptome dynamics of the microRNA inhibition response.Nucleic acids research · 2015Article
- From microRNA target validation to therapy: lessons learned from studies on BDNF.Cellular and molecular life sciences : CMLS · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microarray expression analyses following miRNA transfection/inhibition and, more recently, Argonaute cross-linked immunoprecipitation (CLIP)-seq assays have been used to detect miRNA target sites. CLIP and expression approaches measure differing stages of miRNA functioning-initial binding of the miRNP complex and subsequent message repression. We use nonparametric predictive models to characterize a large number of known target and flanking features, utilizing miRNA transfection, HITS-CLIP, and PAR-CLIP data. In particular, we utilize the precise spatial information provided by CLIP-seq to analyze the predictive effect of target flanking features. We observe distinct target determinants between expression-based and CLIP-based data. Target flanking features such as flanking region conservation are an important AGO-binding determinant-we hypothesize that CLIP experiments have a preference for strongly bound miRNP-target interactions involving adjacent RNA-binding proteins that increase the strength of cross-linking. In contrast, seed-related features are major determinants in expression-based studies, but less so for CLIP-seq studies, and increased miRNA concentrations typical of transfection studies contribute to this difference. While there is a good overlap between miRNA targets detected by miRNA transfection and CLIP-seq, the detection of CLIP-seq targets is largely independent of the level of subsequent mRNA degradation. Also, models built using CLIP-seq data show strong predictive power between independent CLIP-seq data sets, but are not strongly predictive for expression change. Similarly, models built from expression data are not strongly predictive for CLIP-seq data sets, supporting the finding that the determinants of miRNA binding and mRNA degradation differ. Predictive models and results are available at http://servers.binf.ku.dk/antar/.
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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.