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milRNApredictor: Genome-free prediction of fungi milRNAs by incorporating k-mer scheme and distance-dependent pair potential

机译：Milrnapredictor：通过掺入K-MER方案和距离依赖性对潜力，无菌Milrnas的无基因组预测

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摘要

MicroRNA-like small RNAs (milRNAs) with length of 21–22 nucleotides are a type of small non-coding RNAs that are firstly found in Neurospora crassa in 2010. Identifying milRNAs of species without genomic information is a difficult problem. Here, knowledge-based energy features are developed to identify milRNAs by tactfully incorporating k-mer scheme and distance-dependent pair potential. Compared with k-mer scheme, features developed here can alleviate the inherent curse of dimensionality in k-scheme once k becomes large. In addition, milRNApredictor built on novel features performs comparably to k-mer scheme, and achieves sensitivity of 74.21%, and specificity of 75.72% based on 10-fold cross-validation. Furthermore, for novel miRNA prediction, there exists high overlap of results from milRNApredictor and state-of-the-art mirnovo. However, milRNApredictor is simpler to use with reduced requirements of input data and dependencies. Taken together, milRNApredictor can be used to de novo identify fungi milRNAs and other very short small RNAs of non-model organisms.
机译：长度为21-22个核苷酸的MicroRNA样的小RNA（Milrnas）是一种小型非编码RNA，其在2010年在神经孢子菌群中首先发现。鉴定没有基因组信息的物种Milrnas是一个难题。这里，开发了基于知识的能量特征以通过遵守K-MER方案和距离相关的对电位来识别MILRNA。与K-MER方案相比，这里开发的特征可以缓解K-Scheme中的维度的固有诅咒，k变大。此外，基于新颖特征的Milrnapredictor可相当于K-MER方案，基于10倍交叉验证，实现74.21％的灵敏度为74.21％，特异性为75.72％。此外，对于新的miRNA预测，来自Milrnapicictor和最先进的Mirnovo的结果存在高重叠。但是，Milrnapredictor可以更简单地使用输入数据和依赖性的要求。在一起，Milrnapredictor可用于De Novo识别真菌Milrnas和其他非常短的非模型生物的小RNA。

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