Supat Thongjuea. Expert System for Positional Candidate Gene Mining in Oryza Genome: Phase I, Datawarehouse Construction. Master's Degree(Bioinformatics). King Mongkut's University of Technology Thonburi. KMUTT Library.. : King Mongkut's University of Technology Thonburi, 2005.
Expert System for Positional Candidate Gene Mining in Oryza Genome: Phase I, Datawarehouse Construction
Abstract:
After the completion of the rice genome, many publicly useful biological data are
released. Especially, the high-throughput technologies such as microarray, proteomics
and gene-tagging approaches are greatly increasing the volume of information to assist
genes function identification. Most of these biological data are published on the public
domain databases, which are the target of scientists to apply bioinformatics approaches
and data integration systems to find the most promising candidate genes and function of
genes. To utilize heterogeneous rice biological data analyzing for selection the genes of
interest, "RiceGeneThresher", a bioinformatics tool for mining rice biological data, was
developed. RiceGeneThresher consolidates the rice genetics information, genome
annotation, transcriptome, proteome, and metabolome, from the rice biological
information on the public domains. Its system provides a generic datawarehousing
solution for fast and flexible querying rice biological data sets and integration with
third-party data and tools. Its database design and its application interfaces provide a
powerful, flexible tool for the delivery of customized set of rice biological data.
RiceGeneThresher be able to generate supported evidences from each type of "omics"
information that are essential for analyzing and targeting groups or networks of genes
for the interested traits underlying QTLs. This bioinformatic tool is special design for
the rice breeders and rice molecular biologists. However, users ranging from breeders,
laboratory researchers to the experienced molecular biologists and bioinformaticians
can use it in a wide variety of application and scenario to discover and assign the most
promising candidate genes preparation for the further gene functional analysis to
improve the rice cultivars.