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pmid:34232189
Identification of endometriosis-associated genes and pathways based on bioinformatic analysis.
Ting Wang · Ruoan Jiang · Yingsha Yao · Linhua Qian · Yu Zhao · Xiufeng Huang
Medicine · 2021 doi:10.1097/MD.0000000000026530
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Complete file
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The aim of this study was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of endometriosis.The gene expression profiles of GSE25628, GSE5108, and GSE7305 were downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using GEO2R. The database for annotation, visualization, and integrated discovery (DAVID) was utilized to analyze the functional enrichment, gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway of the differentially expressed genes. A protein-protein interaction (PPI) network was constructed and module analysis was performed using search tool for the retrieval of interacting genes and cytoscape.A total of 119 common differentially expressed genes were extracted, consisting of 51 downregulated genes and 68 upregulated genes. 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