Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

aeGEPUCI

General information

URL: http://www.aegep.bio.uci.edu
Full name: aedes aegypti gene expression profile
Description: The database aeGEPUCI integrates microarray analyses of sex- and stage-specific gene expression in Ae, functional gene annotation, genomic sequence data, and computational sequence analysis tools.
Year founded: 2010
Last update:
Version:
Accessibility:
Accessible
Country/Region: United States

Classification & Tag

Data type:
DNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: University of California Irvine
Address:
City:
Province/State:
Country/Region: United States
Contact name (PI/Team): Dr. Sumudu Dissanayake
Contact email (PI/Helpdesk): sdissana@uci.edu

Publications

20920356
aeGEPUCI: a database of gene expression in the dengue vector mosquito, Aedes aegypti. [PMID: 20920356]
Dissanayake SN, Ribeiro JM, Wang MH, Dunn WA, Yan G, James AA, Marinotti O.

BACKGROUND: Aedes aegypti is the principal vector of dengue and yellow fever viruses. The availability of the sequenced and annotated genome enables genome-wide analyses of gene expression in this mosquito. The large amount of data resulting from these analyses requires efficient cataloguing before it becomes useful as the basis for new insights into gene expression patterns and studies of the underlying molecular mechanisms for generating these patterns.
FINDINGS: We provide a publicly-accessible database and data-mining tool, aeGEPUCI, that integrates 1) microarray analyses of sex- and stage-specific gene expression in Ae. aegypti, 2) functional gene annotation, 3) genomic sequence data, and 4) computational sequence analysis tools. The database can be used to identify genes expressed in particular stages and patterns of interest, and to analyze putative cis-regulatory elements (CREs) that may play a role in coordinating these patterns. The database is accessible from the address http://www.aegep.bio.uci.edu.
CONCLUSIONS: The combination of gene expression, function and sequence data coupled with integrated sequence analysis tools allows for identification of expression patterns and streamlines the development of CRE predictions and experiments to assess how patterns of expression are coordinated at the molecular level.

BMC Res Notes. 2010:3() | 51 Citations (from Europe PMC, 2025-12-20)

Ranking

All databases:
3069/6895 (55.504%)
Gene genome and annotation:
954/2021 (52.845%)
3069
Total Rank
51
Citations
3.4
z-index

Community reviews

Not Rated
Data quality & quantity:
Content organization & presentation
System accessibility & reliability:

Word cloud

Related Databases

Citing
Cited by

Record metadata

Created on: 2018-01-27
Curated by:
Nashaiman Pervaiz [2018-12-28]
Yang Zhang [2018-03-27]
Yang Zhang [2018-02-23]
Yang Zhang [2018-02-17]