The purpose of this study was to identify differentially expressed (DE) genes and biological processes associated with changes in gene expression in ankylosing spondylitis (AS). We performed a meta-analysis using the integrative meta-analysis of expression data program on publicly available microarray AS Gene Expression Omnibus (GEO) datasets. We performed Gene Ontology (GO) enrichment analyses and pathway analysis using the Kyoto Encyclopedia of Genes and Genomes. Four GEO datasets, including 31 patients with AS and 39 controls, were available for the meta-analysis.
This study aimed to identify differentially expressed genes (DEGs) of unruptured intracranial aneurysms (IAs) and provide beneficial information for early diagnosis and treatment of IAs. The gene expression profile GSE26969 from the Gene Expression Omnibus database was downloaded, which included six human IA samples: three intracranial arterial aneurysm samples and three normal superficial temporal artery samples (control). Based on these data, we identified the DEGs between normal and disease samples with packages in the R language.
The purpose of this study was to identify critical genes associated with septic multiple trauma by comparing peripheral whole blood samples from multiple trauma patients with and without sepsis. A microarray data set was downloaded from the Gene Expression Omnibus (GEO) database. This data set included 70 samples, 36 from multiple trauma patients with sepsis and 34 from multiple trauma patients without sepsis (as a control set). The data were preprocessed, and differentially expressed genes (DEGs) were then screened for using packages of the R language.
The aim of this study was to identify key genes related to invasive ductal carcinoma (IDC) of the breast by analyzing gene expression data with bioinformatic tools. Microarray data set GSE31138 was downloaded from Gene Expression Omnibus, including 3 breast cancer tissue samples and 3 normal controls. Differentially expressed genes (DEGs) between breast cancer and normal control were screened out (FDR 2). Coexpression between genes was examined with String, and a network was then constructed. Relevant pathways and diseases were retrieved with KOBAS.
To bring about improvements in cancer biology research and elucidate mechanism-based therapeutic targets, we studied the proteome expression profile of purified normal urothelial cells (cancer cells) and normal stromal cells (cancerous stromal cells). Based on the expression profile, biomarker discovery and the mechanisms of multi-step carcinogenesis were explored. We found that 1412/1403 unique proteins commonly appeared in 4 sets of paired cancer/normal tissue, and 1753 proteins were differentially expressed.