- Bioinformatics Analysis: Data from datasets GSE205891 and GSE230002 in the GEO database were mined. Differential expression analysis was performed on each dataset using the online tool GEO2R to identify differentially expressed genes (DEGs). The criteria for identifying DEGs were a fold change of at least 2-fold or less than 0.5-fold, with a p-value < 0.05. The lists of DEGs from both datasets were loaded into R, and the intersection of these lists was determined. GO and KEGG enrichment analyses were conducted on the intersecting genes. Using the STRING protein-protein interaction (PPI) database and Cytoscape software, a PPI network was constructed for the intersecting genes, and the top 10 key genes were identified. The interactions between the proteins encoded by these genes were analyzed to identify those at critical nodes.
生物信息学分析：GEO数据库DEG挖掘与PPI网络关键基因识别
本文详解生物信息学分析全流程，涵盖GSE205891和GSE230002数据集差异表达基因筛选、GO/KEGG富集分析及PPI网络构建，基于STRING数据库和Cytoscape识别关键枢纽基因。
与梅斯小智对话
