An online web server for easy and fast visualization of smoking effects on human lung gene expression. SEGEL integrates 362 samples collected from eight public expression microarray data sets from trachea epithelial cells, large airway epithelial cells, small airway epithelial cells, and alveolar macrophage. Gene expression patterns of regular smokers and nonsmokers across these cells can be queried by gene symbols. Sex difference in response to smoking is also shown. The correlation coefficients between the gene expression and cigarette smoking consumption (the number of packs of cigarettes consumed per year) were also calculated and are shown in the web server. The current version of SEGEL contains around 42,400 annotated gene probe sets represented on the Affymetrix Human Genome U133 Plus 2.0. SEGEL will be an invaluable tool and resource for scientists interested in the effects of smoking on lung gene expression. The web server can be used to identify reliable molecular signatures for drug discovery against smoking-related diseases.
Department of Pharmaceutical Science, College of Pharmacy, University of South Florida, Tampa, FL, USA; Department of Biology, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany; Department of Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, FL, USA; Division of Allergy and Clinical Immunology, College of Medicine, University of South Florida, Tampa, FL, USA
SEGEL funding source(s)
The project was supported by the University of South Florida (USF) System Internal Awards Program under USF Women’s Health Collaborative Grant No. 0095058.