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Bioinformatics databases for rice research
Functional identification of rice on a whole genome scale is required to significantly improve the quality of rice, rice yield, and stress tolerance in response to changing climate. In addition to conventional approaches, new methodologies are required for identification of key genes associated with new agronomical traits. Systems biology is an upcoming trend in the field of functional genomics. Recently, there has been a significant improvement in the resources for systems biology in Oryza sativa (rice), a model crop. These resources include whole genome sequencing/re-sequencing data, transcriptomes, protein-protein interactomes, reactomes, functional gene network tools, and gene indexed mutant populations. The integration of diverse omics data can lead to greater understanding of the functional genomics of rice. Here, we address the development and current progress of the resources available for systems biology in rice: Genome browsers and databases for the orthology identification, transcriptome analysis, protein-protein interaction network and functional gene network analyses, co-expression network, metabolic pathway analysis for promoter analysis, and gene indexed mutants.
