Mining the Bioinformation of Differentially Expressed Genes in Lung Treated with the Hypoxia Based on the Bioinformatics Methods

Objective: To analyze the differentially expressed genes expressed genes in human pulmonary microvascular endothelial cells (HMVEC-L) that cultured in hypoxia environment for getting better understanding of the molecular characteristics caused by hypoxia. Methods: Got the microarray hybridization data from the Gene Expression Omnibus (GEO) database. Identified the differentially expressed genes expressed genes in hypoxic HMVEC-L and the patterns of their regulation using public bioinformatics software and database, which involved BRB-Arraytools, Genecodis, GO and KEGG. Results and Conclusion: These data mining findings between normal and hypoxic HMVEC-L by bioinformatics methods could provide better understanding of the molecular activity change caused by hypoxia.