基于机器学习的miRNA靶标预测方法及相关数据库研究进展OA

MicroRNAs(miRNAs)regulate gene expression by binding to specific sites in the non-coding regions of target RNA.Due to the high-throughput experimental methods to identify miRNA targets are expensive and time-consuming,the development of computational methods that can accurately predict miRNA targets is of great significance.In this paper,we reviewed the methods of miRNA target prediction based on machine learning and miRNA target related databases in recent years.First,we introduced miRNAs and their functions,elucidating the importance of miRNA target prediction.After that,we provided an overview of common miRNA target databases,which provide an essential data for miRNA target prediction.Next,we elaborated the miRNA target prediction methods based on SVM,ensemble learning and deep learning.Finally,we discussed the future challenges and research directions on miRNA target prediction,as well as the potential application of deep learning technology in the field of miRNA target prediction.