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.

长度为21-22个核苷酸的类似MicroRNA的小RNA（milRNA）是一种小型非编码RNA，最早于2010年在crus Neurospora crassa中发现。鉴定没有基因组信息的物种的milRNA是一个难题。在这里，开发了基于知识的能量特征，通过巧妙地结合了k- mer方案和距离依赖性对电位来识别milRNA 。相比ķ聚体方案，此功能可以开发缓解维度中固有的诅咒ķ一次-scheme ķ变大。此外，基于新颖功能的milRNApredictor的性能与k-mer方案，基于10倍交叉验证，可实现74.21％的灵敏度和75.72％的特异性。此外，对于新型miRNA预测，milRNApredictor和最新的mirnovo结果高度重叠。但是，milRNApredictor使用起来更简单，并且减少了对输入数据和相关性的要求。总之，milRNApredictor可用于从头鉴定真菌非模型生物的milRNA和其他非常短的小RNA。