期刊论文

中文

中国药学：英文版

1003-1057

2022

31

12

912-927

National Natural Science Foundation of China （Grant No. 81704061;81173213）； R＆D plan for key areas of Hunan Provincial Department of Science and Technology （Grant No. 2019SK2321）； Hunan Science and Technology Talent Lifting Project （Grant No. 2020TJ-N01）； Hunan Development and Reform Commission Innovation Guidance Project （Hunan Development and Reform Investment 2019-412）； Special Project for the Construction of “Four Seasons Adjusting Yang” Key Laboratory of Mental Diseases in Hunan Provincial Administration of Traditional Chinese Medicine； the “Double First-Class” Discipline Construction Project of Traditional Chinese Medicine in Hunan Province；

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采用Gene Expression Omnibus(GEO)数据集联合机器学习研究急性心肌梗死(acute myocardial infarction,AMI)的差异基因,并预测具有调控作用的潜在成分及中药。从GEO数据...展开更多 采用Gene Expression Omnibus(GEO)数据集联合机器学习研究急性心肌梗死(acute myocardial infarction,AMI)的差异基因,并预测具有调控作用的潜在成分及中药。从GEO数据库下载AMI的人类全基因组数据集(GSE66360和GSE61145),以GSE66360作为测试集,通过R语言的normalize Between Arrays包进行校正后,再调用limma包获取差异基因(DEGs),对DEGs作Gene Ontology(GO)、Kyoto Encyclopedia of Genes and Genomes(KEGG)、Dis...

In the present study,the Gene Expression Omnibus(GEO)dataset combined with machine learning was used to study differential genes in acute myocardial infarction(AMI)and to predict potential components and herbal medicines with regulatory effects.The human genome datasets...MORE In the present study,the Gene Expression Omnibus(GEO)dataset combined with machine learning was used to study differential genes in acute myocardial infarction(AMI)and to predict potential components and herbal medicines with regulatory effects.The human genome datasets of AMI(GSE66360 and GSE61145)were downloaded from t...