Advances in applications of artificial intelligence algorithms for cancer-related miRNA research

VernacularTitle:人工智能算法在癌症相关微RNA研究中的应用进展
Author: Hongyu LU ¹ ; Jia ZHANG ; Yixin CAO ; Shuming WU ; Yuan WEI ; Runting YIN
Author Information

1. 江苏大学药学院,江苏镇江 212013
Keywords: MicroRNA; Machine learning; Deep learning; Target prediction; Subcellular distribution; Clinical prediction model; Review
From: Journal of Zhejiang University. Medical sciences 2024;53(2):231-243
CountryChina
Language:Chinese
Abstract: MiRNAs are a class of small non-coding RNAs,which regulate gene expression post-transcriptionally by partial complementary base pairing.Aberrant miRNA expressions have been reported in tumor tissues and peripheral blood of cancer patients.In recent years,artificial intelligence algorithms such as machine learning and deep learning have been widely used in bioinformatic research.Compared to traditional bioinformatic tools,miRNA target prediction tools based on artificial intelligence algorithms have higher accuracy,and can successfully predict subcellular localization and redistribution of miRNAs to deepen our understanding.Additionally,the construction of clinical models based on artificial intelligence algorithms could significantly improve the mining efficiency of miRNA used as biomarkers.In this article,we summarize recent development of bioinformatic miRNA tools based on artificial intelligence algorithms,focusing on the potential of machine learning and deep learning in cancer-related miRNA research.