生物信息学2026，Vol.24Issue(1)：1-13,13.DOI:10.12113/202409006
基于机器学习的miRNA靶标预测方法及相关数据库研究进展
Recent development of machine learning-based miRNA target prediction methods and related databases
摘要
Abstract
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.关键词
miRNA/机器学习/深度学习/miRNA靶标预测/miRNA相关靶标数据库Key words
miRNA/Machine learning/Deep learning/miRNA target prediction/miRNA target database分类
生物科学引用本文复制引用
蒋辉,罗思杰..基于机器学习的miRNA靶标预测方法及相关数据库研究进展[J].生物信息学,2026,24(1):1-13,13.基金项目
湖南省教育厅科学研究项目(No.24A0299) （No.24A0299）
南华大学博士科研启动基金(No.220XQD048). （No.220XQD048）
