机器学习在肠道菌群二代测序数据分析中的应用  

Application of machine learning to the analysis of next-generation sequencing data of intestinal flora

作　　者：王家欣 孙淼[1] 周琪[1] 许建成[1] Wang Jiaxin;Sun Miao;Zhou Qi;Xu Jiancheng(Department of Laboratory Medicine,First Hospital,Jilin University,Changchun 130021,China)

机构地区：[1]吉林大学第一医院检验科,长春130021

出　　处：《中华检验医学杂志》2025年第2期186-191,共6页Chinese Journal of Laboratory Medicine

基　　金：吉林省科技发展计划项目医药健康专项(20220401085YY)。

摘　　要：宏基因组二代测序作为一种无偏倚的检测技术,展现出较传统方法更高的诊断效能。肠道微生物是保障身体健康的重要菌群,成为目前的研究热点。利用机器学习对肠道菌群基因组数据进行建模、分析,在疾病预测与诊断中非常重要。本文简要介绍宏基因组二代测序技术的特点、机器学习的关键算法及评估指标,概述机器学习与宏基因组二代测序结合的主要步骤,总结机器学习与宏基因组二代测序技术结合在肠道菌群研究中的应用,为相关疾病的诊断和预测提供更准确的方法,给未来的研究和临床实践提供更多的思路。Metagenomic next-generation sequencing,as an unbiased detection technology,demonstrates higher diagnostic efficacy than traditional methods.Gut microorganisms are important flora for safeguarding health and have become a hot research topic.Modeling and analyzing the genomic data of intestinal flora using machine learning is very important in disease prediction and diagnosis.This paper briefly introduces the characteristics of metagenomic next-generation sequencing,key algorithms and evaluation indexes of machine learning,outlines the main steps of combining machine learning with metagenomic next-generation sequencing,and summarizes the application of the combination of machine learning and metagenomic next-generation sequencing technology in the study of intestinal flora,which will provide a more accurate method for diagnosis and prediction of the related diseases,and give more ideas for the future research and clinical practice.

关 键 词：宏基因组 二代测序 机器学习 肠道菌群 生物标志物 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] R318[自动化与计算机技术—控制科学与工程]