Database
angaGEDUCI: Anopheles gambiae gene expression database with integrated comparative algorithms for identifying conserved DNA motifs in promoter sequences
-
* Corresponding author: Anthony A James aajames@uci.edu
1 Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697, USA
2 Laboratory of Malaria and Vector Research, National Institutes of Health (NIH/NIAID), Rockville, MD 20852, USA
3 Department of Microbiology and Molecular Genetics, University of California, Irvine, CA 92697, USA
BMC Genomics 2006, 7:116 doi:10.1186/1471-2164-7-116
Published: 17 May 2006Abstract
Background
The completed sequence of the Anopheles gambiae genome has enabled genome-wide analyses of gene expression and regulation in this principal vector of human malaria. These investigations have created a demand for efficient methods of cataloguing and analyzing the large quantities of data that have been produced. The organization of genome-wide data into one unified database makes possible the efficient identification of spatial and temporal patterns of gene expression, and by pairing these findings with comparative algorithms, may offer a tool to gain insight into the molecular mechanisms that regulate these expression patterns.
Description
We provide a publicly-accessible database and integrated data-mining tool, angaGEDUCI, that unifies 1) stage- and tissue-specific microarray analyses of gene expression in An. gambiae at different developmental stages and temporal separations following a bloodmeal, 2) functional gene annotation, 3) genomic sequence data, and 4) promoter sequence comparison algorithms. The database can be used to study genes expressed in particular stages, tissues, and patterns of interest, and to identify conserved promoter sequence motifs that may play a role in the regulation of such expression. The database is accessible from the address http://www.angaged.bio.uci.edu webcite.
Conclusion
By combining gene expression, function, and sequence data with integrated sequence comparison algorithms, angaGEDUCI streamlines spatial and temporal pattern-finding and produces a straightforward means of developing predictions and designing experiments to assess how gene expression may be controlled at the molecular level.