基于GEO数据库芯片的心肌梗死标志物的筛选与生物信息学分析
| 作者: |
1魏文,
2汪逵
1 恩施土家族苗族自治州中心医院内科心血管中心，湖北 恩施 445000 2 恩施土家族苗族自治州中心医院神经外科，湖北 恩施 445000 |
| 通讯: |
汪逵
Email: wangkuixinnei@163.com |
| DOI: | 10.3978/j.issn.2095-6959.2019.01.005 |
摘要
目的：对首次急性心肌梗死(acute myocardial infarction，AMI)患者基因芯片数据进行生物信息学分析，寻找表达特征基因谱。方法：利用GEO数据库中高通量基因芯片数据筛选出AMI信息的芯片。采用GO基因功能注释并进行蛋白质相互作用网络可视化分析。结果：经过数据分析，这些差异性表达的基因被富集到不同的生物学过程或分子功能的子集中。结论：通过对GEO数据库中AMI的表达数据分析研究而选出的22个差异表达基因，可为该疾病的早期诊断治疗和靶向药物的开发提供重要理论依据。
关键词：
心肌梗死；生物信息学；GEO数据库
Screening and bioinformatics analysis of myocardial infarction markers Based on GEO database chip
CorrespondingAuthor: WANG Kui Email: wangkuixinnei@163.com
DOI: 10.3978/j.issn.2095-6959.2019.01.005
Abstract
Objective: To perform bioinformatics analysis on the gene chip data of patients with first acute myocardial infarction (AMI) to find the gene expression profile. Methods: We used the high-throughput gene chip data in the GEO database to screen out the AMI information chip. The GO gene function was used for annotation and visual analysis of the protein interaction network. Results: After data analysis, these differentially expressed genes were enriched in subsets of different biological processes or molecular functions. Conclusion: Twenty-two differentially expressed genes were selected by analyzing the expression data of AMI in the GEO database, which can provide an important theoretical basis for the early diagnosis and treatment of this disease and the development of targeted drugs.
Keywords：
myocardial infarction; bioinformatics; GEO database