|Wang, Yong - MISSISSIPPI STATE UNIV|
|Hodges, Julia - MISSISSIPPI STATE UNIV|
|Bridges, Susan - MISSISSIPPI STATE UNIV|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: October 13, 2003
Publication Date: October 13, 2003
Citation: Wang, Y., Hodges, J.E., Bridges, S.M., Williams, W.P., Brooks, T.D., Windham, G.L. 2003. An integrated data management system supporting aflatoxin studies [abstract]. Multicrop Aflatoxin and Fumoninsin Elimination and Fungal Genomics Workshop Proceedings. p. 65. Technical Abstract: An on-going project in the Corn Host Plant Resistance Research Unit of the United States Department of Agriculture - Agricultural Research Service (USDA-ARS) at Mississippi State University is intended to determine the effects of biotic and abiotic factors on Aspergillus flavus infection and aflatoxin accumulation on maize and develop maize cell lines with resistance to the insect damage, A. flavus infection, and aflatoxin accumulation. An integrated database system with data management, data mining, and data modeling capabilities to support this project has been constructed by the Intelligent Systems Laboratory of the Department of Computer Science and Engineering at Mississippi State University (MSU). This database differs from other existing databases by providing a comprehensive view of the maize genetics research at MSU and archiving not only raw data, but also derived data and metadata collected or generated by the biologists. The database system consists of five partitions: germplasm data, field data, quantitative trait loci (QTL) analysis data, proteomics data, and weather data. A user-friendly web-based interface has been designed to provide quick and flexible access to the database system for investigators. This database system is compatible with several existing database systems, such as GRIN database (Germplasm Resources Information Network, http://www.ars-grin.gov/npgs/), MaizeGDB (Maize Genetics and Genomics Database, http://www.maizegdb.org/) and the PEDRo proteomics database model (http://pedro.man.ac.uk/), to facilitate the import and export of data.