首页|大规模基因表达谱技术在中药现代化研究中的应用现状

大规模基因表达谱技术在中药现代化研究中的应用现状

扫码查看
大规模基因表达谱技术通过生成或整合大量药物诱导的基因表达数据,并运用人工智能算法进行匹配分析,以识别药物-基因及疾病间的复杂关系和功能网络,推动药物研究的发展.中药因其多成分、多靶点、多途径的复杂作用机制,传统的研究方法往往难以全面解析其生物学效应.基于大规模基因表达谱融合人工智能的药物研发策略展现了独特优势,其核心在于无需依赖特定药物靶点或作用机制等先验知识.该文全面综述了大规模基因表达谱技术在中药研究中的创新性应用,同时概述了大规模基因表达谱的发展历程、模式匹配算法优化及相关数据库建设方面的最新进展.总而言之,基于大规模基因表达谱融合人工智能技术为中药的现代化应用和理论创新提供了一种强有力的假设生成工具.
Application of large-scale gene expression profiling in modern research of traditional Chinese medicine
Large-scale gene expression profiling generates or integrates massive data of gene expression under drug induction and employs artificial intelligence algorithms for pattern matching and association analysis.This approach facilitates the identification of complex relationships and functional networks between drugs,genes,and diseases,thereby significantly advancing drug research.Traditional Chinese medicine (TCM),with its characteristic multi-component,multi-target,and multi-pathway mechanisms,poses challenges to conventional methodologies in the comprehensive elucidation of its biological effects.The drug discovery strategy that combines large-scale gene expression profiling with artificial intelligence offers distinct advantages since it does not need the prior knowledge of specific drug targets or mechanisms.This article comprehensively reviews the innovative applications of large-scale gene expression profiling in TCM research as well as the recent advancements in the development of these technologies,the optimization of pattern matching algorithms,and the construction of related databases.In summary,the integration of large-scale gene expression profiling with artificial intelligence provides a powerful hypothesis-generating tool for the modern application and theoretical innovation of TCM.

large-scale gene expression profilestraditional Chinese medicineartificial intelligence algorithmspattern matching

陈凤鸣、赵冉冉、韩星星、李欢、唐志书

展开 >

中国中医科学院中药资源中心道地药材品质保障与资源持续利用全国重点实验室,北京 100700

北京中医药大学,北京 100029

大规模基因表达谱 中药 人工智能算法 模式匹配

2024

中国中药杂志
中国药学会

中国中药杂志

CSTPCD北大核心
影响因子:1.718
ISSN:1001-5302
年,卷(期):2024.49(23)