首页|人工智能算法在癌症相关微RNA研究中的应用进展

人工智能算法在癌症相关微RNA研究中的应用进展

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微RNA(miRNA)是一类通过不完全碱基互补配对实现后转录调控作用的小分子非编码RNA，其往往在癌症患者的病灶和外周血中表达失调。近年来，基于人工智能算法如机器学习和深度学习的模型逐渐应用于miRNA生物信息学研究。与传统的生物信息学工具比较，基于人工智能算法的miRNA靶点预测工具准确度更高，并实现了miRNA亚细胞定位和亚细胞重分布的预测，进一步深化了科研人员对miRNA的认识。此外，人工智能算法在临床模型构建的应用也显著提升了miRNA生物标志物的挖掘效率。本文总结了近年来人工智能算法在miRNA靶点预测、亚细胞定位和生物标志物挖掘的应用，并探讨了机器学习和深度学习对癌症相关miRNA研究的潜在价值。
Advances in applications of artificial intelligence algorithms for cancer-related miRNA research
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.

MicroRNAMachine learningDeep learningTarget predictionSubcellular distributionClinical prediction modelReview

鲁洪宇、张佳、曹一鑫、吴书铭、魏渊、殷润婷

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江苏大学药学院,江苏 镇江 212013

江苏大学附属医院肿瘤内科,江苏 镇江 212013

微RNA 机器学习 深度学习 靶点预测 亚细胞分布 临床预测模型 综述

国家重点研发计划中央本级重大增减支项目镇江市重点研发计划(社会发展)江苏大学高级人才科研启动基金江苏省研究生科研与实践创新计划江苏大学大学生创新创业训练计划

2022TFE02051002060302-2004-09SH202003621JDG022KYCX23_3752202310299479X

2024

10.3724/zdxbyxb-2023-0511

浙江大学学报(医学版)
浙江大学

浙江大学学报(医学版)

CSTPCD北大核心
影响因子：0.926
ISSN：1008-9292
年,卷(期)：2024.53(2)
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