Tsukuba Life Science Innovation Program, University of Tsukuba, Tsukuba 3058577, Japan.
School of Healthcare Technology, Chengdu Neusoft University, 611844, Chengdu, China.
Brief Bioinform. 2022 Sep 20;23(5). doi: 10.1093/bib/bbac395.
The location of microRNAs (miRNAs) in cells determines their function in regulation activity. Studies have shown that miRNAs are stable in the extracellular environment that mediates cell-to-cell communication and are located in the intracellular region that responds to cellular stress and environmental stimuli. Though in situ detection techniques of miRNAs have made great contributions to the study of the localization and distribution of miRNAs, miRNA subcellular localization and their role are still in progress. Recently, some machine learning-based algorithms have been designed for miRNA subcellular location prediction, but their performance is still far from satisfactory. Here, we present a new data partitioning strategy that categorizes functionally similar locations for the precise and instructive prediction of miRNA subcellular location in Homo sapiens. To characterize the localization signals, we adopted one-hot encoding with post padding to represent the whole miRNA sequences, and proposed a deep bidirectional long short-term memory with the multi-head self-attention algorithm to model. The algorithm showed high selectivity in distinguishing extracellular miRNAs from intracellular miRNAs. Moreover, a series of motif analyses were performed to explore the mechanism of miRNA subcellular localization. To improve the convenience of the model, a user-friendly web server named iLoc-miRNA was established (http://iLoc-miRNA.lin-group.cn/).
miRNAs（微 RNA）在细胞中的位置决定了它们在调节活性中的功能。研究表明，miRNAs 在介导细胞间通讯的细胞外环境中稳定存在，并且位于对细胞应激和环境刺激做出反应的细胞内区域。尽管 miRNA 的原位检测技术为 miRNA 的定位和分布研究做出了巨大贡献，但 miRNA 的亚细胞定位及其作用仍在研究中。最近，一些基于机器学习的算法已被设计用于 miRNA 亚细胞定位预测，但它们的性能仍远未令人满意。在这里，我们提出了一种新的数据分区策略，该策略将功能相似的位置进行分类，以精确和有指导地预测人类 miRNA 的亚细胞定位。为了描述定位信号，我们采用了独热编码和后填充来表示整个 miRNA 序列，并提出了一种深度双向长短期记忆与多头自注意力算法来进行建模。该算法在区分细胞外 miRNA 和细胞内 miRNA 方面表现出很高的选择性。此外，还进行了一系列的基序分析来探索 miRNA 亚细胞定位的机制。为了提高模型的便利性，我们建立了一个用户友好的网络服务器 iLoc-miRNA（http://iLoc-miRNA.lin-group.cn/）。
