ArticlePloS one2009
Reexamining microRNA site accessibility in Drosophila: a population genomics study.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- The sequence features that define efficient and specific hAGO2-dependent miRNA silencing guides.Nucleic acids research · 2018Article
- A Noninvasive Test for MicroRNA Expression in Oral Squamous Cell Carcinoma.International journal of molecular sciences · 2018Article
- MicroRNA duplication accelerates the recruitment of new targets during vertebrate evolution.RNA (New York, N.Y.) · 2018Article
- Evolution and genomic organization of muscle microRNAs in fish genomes.BMC evolutionary biology · 2014Article
- MiRmap: comprehensive prediction of microRNA target repression strength.Nucleic acids research · 2012Article
- Article
- MicroRNA transfection and AGO-bound CLIP-seq data sets reveal distinct determinants of miRNA action.RNA (New York, N.Y.) · 2011Article
- Assessing the utility of thermodynamic features for microRNA target prediction under relaxed seed and no conservation requirements.PloS one · 2011Article
- Correlating gene expression variation with cis-regulatory polymorphism in Saccharomyces cerevisiae.Genome biology and evolution · 2010Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kertesz et al. (Nature Genetics 2008) described PITA, a miRNA target prediction algorithm based on hybridization energy and site accessibility. In this note, we used a population genomics approach to reexamine their data and found that the PITA algorithm had lower specificity than methods based on evolutionary conservation at comparable levels of sensitivity.We also showed that deeply conserved miRNAs tend to have stronger hybridization energies to their targets than do other miRNAs. Although PITA had higher specificity in predicting targets than a naïve seed-match method, this signal was primarily due to the use of a single cutoff score for all miRNAs and to the observed correlation between conservation and hybridization energy. Overall, our results clarify the accuracy of different miRNA target prediction algorithms in Drosophila and the role of site accessibility in miRNA target prediction.
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Registered trials
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