AUTHOR=Luo Yuxun , Peng Li , Shan Wenyu , Sun Mengyue , Luo Lingyun , Liang Wei TITLE=Machine learning in the development of targeting microRNAs in human disease JOURNAL=Frontiers in Genetics VOLUME=13 YEAR=2023 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1088189 DOI=10.3389/fgene.2022.1088189 ISSN=1664-8021 ABSTRACT=

A microRNA is a small, single-stranded, non-coding ribonucleic acid that plays a crucial role in RNA silencing and can regulate gene expression. With the in-depth study of miRNA in development and disease, miRNA has become an attractive target for novel therapeutic strategies. Exploring miRNA targeting therapy only through experiments is expensive and laborious, so it is essential to develop novel and efficient computational methods to narrow down the search. Recent advances in machine learning applied in biomedical informatics provide opportunities to explore miRNA-targeting drugs, thus promoting miRNA therapeutics. This review provides an overview of recent advancements in miRNA targeting therapeutic using machine learning. First, we mainly describe the basics of predicting miRNA targeting drugs, including pharmacogenomic data resources and data preprocessing. Then we present primary machine learning algorithms and elaborate their application in discovering relationships among miRNAs, drugs, and diseases. Along with the progress of miRNA targeting therapeutics, we finally analyze and discuss the current challenges and opportunities that machine learning confronts.