ArticleNucleic acids research2014
miRdentify: high stringency miRNA predictor identifies several novel animal miRNAs.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Computational identification and validation of non-coding rna biomarkers in gastrointestinal cancer.Functional & integrative genomics · 2025Review
- Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets.Functional & integrative genomics · 2023Review
- MicroRNAs Regulating Autophagy in Neurodegeneration.Advances in experimental medicine and biology · 2021Article
- Trends in the development of miRNA bioinformatics tools.Briefings in bioinformatics · 2019Review
- miRNA analysis with Prost! reveals evolutionary conservation of organ-enriched expression and post-transcriptional modifications in three-spined stickleback and zebrafish.Scientific reports · 2019Article
- Analysis of -5p and -3p Strands of miR-145 and miR-140 During Mesenchymal Stem Cell Chondrogenic Differentiation.Tissue engineering. Part A · 2019Article
- A Review on Recent Computational Methods for Predicting Noncoding RNAs.BioMed research international · 2017Review
- Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.BMC bioinformatics · 2016Article
- Novel equine tissue miRNAs and breed-related miRNA expressed in serum.BMC genomics · 2016Article
- Computational Prediction of miRNA Genes from Small RNA Sequencing Data.Frontiers in bioengineering and biotechnology · 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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During recent years, miRNAs have been shown to play important roles in the regulation of gene expression. Accordingly, much effort has been put into the discovery of novel uncharacterized miRNAs in various organisms. miRNAs are structurally defined by a hairpin-loop structure recognized by the two-step processing apparatus, Drosha and Dicer, necessary for the production of mature ∼ 22-nucleotide miRNA guide strands. With the emergence of high-throughput sequencing applications, tools have been developed to identify miRNAs and profile their expression based on sequencing reads. However, as the read depth increases, false-positive predictions increase using established algorithms, underscoring the need for more stringent approaches. Here we describe a transparent pipeline for confident miRNA identification in animals, termed miRdentify. We show that miRdentify confidently discloses more than 400 novel miRNAs in humans, including the first male-specific miRNA, which we successfully validate. Moreover, novel miRNAs are predicted in the mouse, the fruit fly and nematodes, suggesting that the pipeline applies to all animals. The entire software package is available at www.ncrnalab.dk/mirdentify.
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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.