College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China.
College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China.
Brief Bioinform. 2022 Mar 10;23(2). doi: 10.1093/bib/bbac044.
Subcellular localization of microRNAs (miRNAs) is an important reflection of their biological functions. Considering the spatio-temporal specificity of miRNA subcellular localization, experimental detection techniques are expensive and time-consuming, which strongly motivates an efficient and economical computational method to predict miRNA subcellular localization. In this paper, we describe a computational framework, MiRLoc, to predict the subcellular localization of miRNAs. In contrast to existing methods, MiRLoc uses the functional similarity between miRNAs instead of sequence features and incorporates information about the subcellular localization of the corresponding target mRNAs. The results show that miRNA functional similarity data can be effectively used to predict miRNA subcellular localization, and that inclusion of subcellular localization information of target mRNAs greatly improves prediction performance.
miRNAs（microRNAs）的亚细胞定位是反映其生物学功能的一个重要方面。鉴于 miRNA 亚细胞定位的时空特异性，实验检测技术既昂贵又耗时，这强烈促使我们开发出一种高效且经济的计算方法来预测 miRNA 亚细胞定位。在本文中，我们描述了一种计算框架 MiRLoc，用于预测 miRNAs 的亚细胞定位。与现有方法不同，MiRLoc 使用 miRNA 之间的功能相似性，而不是序列特征，并整合了相应靶 mRNA 亚细胞定位的信息。结果表明，miRNA 功能相似性数据可有效地用于预测 miRNA 亚细胞定位，并且包含靶 mRNA 亚细胞定位信息可极大地提高预测性能。
