ArticleNature communications2017
On the performance of pre-microRNA detection algorithms.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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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
21 citing papers in PubMed.
- De Novo Sequencing of Peptides from Tandem Mass Spectra and Applications in Proteogenomics.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Description Generation Using Variational Auto-Encoders for Precursor microRNA.Entropy (Basel, Switzerland) · 2024Article
- Hepatitis B Virus and microRNAs: A Bioinformatics Approach.International journal of molecular sciences · 2023Review
- Accurate microRNA annotation of animal genomes using trained covariance models of curated microRNA complements in MirMachine.Cell genomics · 2023Article
- Community-wide collaboration is a must to reinstall trust in bioinformatics solutions and biomedical interpretation.Journal of integrative bioinformatics · 2023Article
- Deep learning in bioinformatics.Turkish journal of biology = Turk biyoloji dergisi · 2023Article
- Computational Detection of Pre-microRNAs.Methods in molecular biology (Clifton, N.J.) · 2022Review
- A hybrid CNN-LSTM model for pre-miRNA classification.Scientific reports · 2021Article
- Circular RNA-MicroRNA-MRNA interaction predictions in SARS-CoV-2 infection.Journal of integrative bioinformatics · 2021Article
- Novel perspectives for SARS-CoV-2 genome browsing.Journal of integrative bioinformatics · 2021Article
- Genome-wide computational prediction of miRNAs in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) revealed target genes involved in pulmonary vasculature and antiviral innate immunity.Molecular biology research communications · 2020Article
- Deep neural networks for human microRNA precursor detection.BMC bioinformatics · 2020Article
- Analysis of conserved miRNAs in cynomolgus macaque genome using small RNA sequencing and homology searching.PeerJ · 2020Article
- Article
- Genome-wide hairpins datasets of animals and plants for novel miRNA prediction.Data in brief · 2019Article
- Nucleotide-level Convolutional Neural Networks for Pre-miRNA Classification.Scientific reports · 2019Article
- MicroRNA prediction based on 3D graphical representation of RNA secondary structures.Turkish journal of biology = Turk biyoloji dergisi · 2019Article
- Computational prediction of miRNAs in Nipah virus genome reveals possible interaction with human genes involved in encephalitis.Molecular biology research communications · 2018Article
- Distinguishing mirtrons from canonical miRNAs with data exploration and machine learning methods.Scientific reports · 2018Article
- Identification of microRNAs associated with the exogenous spermidine-mediated improvement of high-temperature tolerance in cucumber seedlings (Cucumis sativus L.).BMC genomics · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs are crucial for post-transcriptional gene regulation, and their dysregulation has been associated with diseases like cancer and, therefore, their analysis has become popular. The experimental discovery of miRNAs is cumbersome and, thus, many computational tools have been proposed. Here we assess 13 ab initio pre-miRNA detection approaches using all relevant, published, and novel data sets while judging algorithm performance based on ten intrinsic performance measures. We present an extensible framework, izMiR, which allows for the unbiased comparison of existing algorithms, adding new ones, and combining multiple approaches into ensemble methods. In an exhaustive attempt, we condense the results of millions of computations and show that no method is clearly superior; however, we provide a guideline for biomedical researchers to select a tool. Finally, we demonstrate that combining all of the methods into one ensemble approach, for the first time, allows reliable purely computational pre-miRNA detection in large eukaryotic genomes.As the experimental discovery of microRNAs (miRNAs) is cumbersome, computational tools have been developed for the prediction of pre-miRNAs. Here the authors develop a framework to assess the performance of existing and novel pre-miRNA prediction tools and provide guidelines for selecting an appropriate approach for a given data set.
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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.