MicroRNAs form an essential class of post-transcriptional gene regulator of eukaryotic species, and play critical parts in development and disease and stress responses. MicroRNAs may originate from various genomic loci, have structural characteristics, and appear in canonical or modified forms, making them subtle to detect and analyze. We present miRvial, a robust computational method and companion software package that supports parameter adjustment and visual inspection of candidate microRNAs. Extensive results comparing miRvial and six existing microRNA finding methods on six model organisms, Mus musculus, Drosophila melanogaste, Arabidopsis thaliana, Oryza sativa, Physcomitrella patens and Chlamydomonas reinhardtii, demonstrated the utility and rigor of miRvial in detecting novel microRNAs and characterizing features of microRNAs. Experimental validation of several novel microRNAs in C. reinhardtii that were predicted by miRvial but missed by the other methods illustrated the superior performance of miRvial over the existing methods. miRvial is open source and available at https://github.com/SystemsBiologyOfJianghanUniversity/miRvial.

中文翻译：

---

通过miRvial检测和表征各种基因组来源的microRNA

MicroRNA构成真核物种转录后基因调节剂的重要类别，并在发育，疾病和应激反应中发挥关键作用。MicroRNA可能源自各种基因组位点，具有结构特征，并以典范或修饰形式出现，使其难以检测和分析。我们介绍了miRvial，它是一种强大的计算方法和配套软件包，支持参数调整和候选microRNA的目测检查。比较miRvial丰富的成果和六个模式生物，现有的六个小RNA的发现方法小家鼠，果蝇melanogaste，拟南芥，水稻，小立碗藓和莱茵衣藻证明了miRvial在检测新型microRNA和表征microRNA特征方面的实用性和严格性。由miRvial预测但在其他方法中未见到的对莱茵衣藻中的几种新型microRNA的实验验证表明，miRvial的性能优于现有方法。miRvial是开源的，可从https://github.com/SystemsBiologyOfJianghanUniversity/miRvial获得。