ArticleNucleic acids research2012
A fast ab-initio method for predicting miRNA precursors in genomes.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.
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- Identification and bioinformatic functional analysis of novel and known polymorphisms in the myostatin gene of Ukrainian Carpathian Mountain sheep.Scientific reports · 2026Article
- An Overview of miRNA and miRNA Target Analysis Tools.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Uncovering chikungunya virus-encoded miRNAs and host-specific targeted genes associated with antiviral immune responses: an integrated bioinformatics approach.Scientific reports · 2024Article
- Hepatitis B Virus and microRNAs: A Bioinformatics Approach.International journal of molecular sciences · 2023Review
- A gain-of-function mutation in microRNA 142 is sufficient to cause the development of T-cell leukemia in mice.Cancer science · 2023Article
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- Transposable elements contribute to the spatiotemporal microRNA landscape in human brain development.RNA (New York, N.Y.) · 2022Article
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- Computational Detection of Pre-microRNAs.Methods in molecular biology (Clifton, N.J.) · 2022Review
- MicroRNA-Mediated Regulation of the Virus Cycle and Pathogenesis in the SARS-CoV-2 Disease.International journal of molecular sciences · 2021Article
- In silico analysis suggests the RNAi-enhancing antibiotic enoxacin as a potential inhibitor of SARS-CoV-2 infection.Scientific reports · 2021Article
- A Brief Survey for MicroRNA Precursor Identification Using Machine Learning Methods.Current genomics · 2020Review
- Identification and co-evolution pattern of stem cell regulator miR394s and their targets among diverse plant species.BMC evolutionary biology · 2019Article
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- Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.BMC bioinformatics · 2016Article
- Ebola virus encodes a miR-155 analog to regulate importin-α5 expression.Cellular and molecular life sciences : CMLS · 2016Article
- miRNAFold: a web server for fast miRNA precursor prediction in genomes.Nucleic acids research · 2016Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
miRNAs are small non coding RNA structures which play important roles in biological processes. Finding miRNA precursors in genomes is therefore an important task, where computational methods are required. The goal of these methods is to select potential pre-miRNAs which could be validated by experimental methods. With the new generation of sequencing techniques, it is important to have fast algorithms that are able to treat whole genomes in acceptable times. We developed an algorithm based on an original method where an approximation of miRNA hairpins are first searched, before reconstituting the pre-miRNA structure. The approximation step allows a substantial decrease in the number of possibilities and thus the time required for searching. Our method was tested on different genomic sequences, and was compared with CID-miRNA, miRPara and VMir. It gives in almost all cases better sensitivity and selectivity. It is faster than CID-miRNA, miRPara and VMir: it takes ≈ 30 s to process a 1 MB sequence, when VMir takes 30 min, miRPara takes 20 h and CID-miRNA takes 55 h. We present here a fast ab-initio algorithm for searching for pre-miRNA precursors in genomes, called miRNAFold. miRNAFold is available at http://EvryRNA.ibisc.univ-evry.fr/.
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