Abstract
Purpose: :
The increasing numbers of genomics and proteomics databases and microarray data provide researchers with vast resources of information that can be utilized to enhance their research. To make better use of these resources, we developed a web application to map, customize, and share data sources, as well as extract relevant, curated PubMed literature index.
Methods: :
Gene2function.com web service was designed as a tab-executable system using the Web Server .NET 2.0 Framework and SQL Server 2005. The original source databases (Entrez Gene, Rat Genome Database, PantherDB, GenAge aging database, Secretory Protein Database (SPD), GO-Slim for molecular function, biological process, cellular component) were downloaded, formatted and converted into one-to-one respective fields in the SQL database table. The lacrimal gland data source from the National Eye Institute (NEI) was also included. The "Upload" and "Share" database functions allow a registered user the option to upload and share up to five genomics/proteomics data sources with their collaborators. An empty field allows a user to include other relevant information (p-value, fold change, call) to their customized database. The NCBI Gene Reference into Function (GenRIF) tab retrieve corresponding curated PubMed abstracts, with a sort-by-year function.
Results: :
All functions were thoroughly tested using microarray data results from Affymetrix and Applied Biosystems. A user submits an input file (gene symbol or GenBank ID) and select the desired databases, and after selecting the tab for Annotation or GenRIF, the search engine goes through a routine to retrieve the results. The upload database function provides researcher a downloadable Excel spreadsheet, using copy/paste functions to format their database. This function will also enable researchers to upload other freely available data sources.
Conclusions: :
The web service provides an easy to use platform to customize and exchange research-specific microarray data and external databases. It also enable a researcher to cross-validate results, irrespective of the microarray platform. Additional functions will be evaluated and added based on the needs of the research community.
Keywords: gene mapping • aging • gene microarray