Smoking Effects on Gene Expression of Lungs (SEGEL)
Please input the gene symbol* (For example DUOX2, or HSPA6):
All genes included in the SEGEL database could be found here.
*If you cannot find the genes you are interested in, please check their official gene symbols at www.genecards.com
You may enter multiple offical gene symbols separated by spaces for the batch searching of the TIBS database (for example "ADORA2B HSPA6 PPARG").
You may enter a SINGLE query string for the fuzzy searching of the TIBS database (For example, "ADOR" or "HSPA").
About the database
Cigarette smoking is considered the major risk factor for many lung diseases particularly, chronic obstructive pulmonary diseases (COPD) and lung cancer. Expression microarray techniques have been widely applied to detect the smoking effects on gene expression in different human cells in the lungs. These projects have provided a lot of useful information for researchers to understand the potential molecular mechanism(s) of smoke-induced pathogenesis. However, a user-friendly database which would allow scientists to query these data sets and compare the smoking effects on gene expression across different cells has not yet been established. For that reason, we have integrated eight public expression microarray data from trachea epithelial cells, large airway epithelial cells, small airway epithelial cells, and alveolar macrophage into an online database called SEGEL (Smoking Effects on Gene Expression of Lung).
Users can query spatiotemporal gene expression patterns across these cells or tissues from smokers and non-smokers by gene symbols, and find the effects of smoking cigarettes on the gene expression of lungs in this database. Sex difference in response to smoking was also shown. The correlation coefficients between the gene expression and cigarette smoking consumption were calculated and shown in the database.
The current version of SEGEL database contains 42,400 annotated gene probe sets represented on the Affymetrix Human Genome U133 plus 2.0 platform. SEGEL will be an invaluable resource for researchers interested in the effects of smoking on gene expression in the lungs, and in drug development against smoking-related diseases.
Download source data here:
This project was supported by the USF Women's Health Seed Grant Awards (No. 0095058) and the USF College of Pharmacy research start-up grant