OsPAD is a systemic proteome annotation database for Oryza sativa with integrated rice proteomics data on the basis of two-dimensional polyacrylamide gel electrophoresis. The mission of OsPAD is to provide the biologists with a comprehensive and freely accessible resource of rice's proteomic information together with several online tools.

  MicroRNAs (miRNAs), one type of small RNAs (sRNAs) in plants, play an essential role in gene regulation. Several miRNA databases were established; however, successively generated new datasets need to be collected, organized and analyzed. To this end, we have constructed a plant miRNA knowledge base (PmiRKB) that provides four major functional modules. In the 'SNP' module, single nucleotide polymorphism (SNP) data of seven Arabidopsis (Arabidopsis thaliana) accessions and 21 rice (Oryza sativa) subspecies were collected to inspect the SNPs within pre-miRNAs (precursor microRNAs) and miRNA¡ªtarget RNA duplexes. Depending on their locations, SNPs can affect the secondary structures of pre-miRNAs, or interactions between miRNAs and their targets. A second module, 'Pri-miR', can be used to investigate the tissue-specific, transcriptional contexts of pre- and pri-miRNAs (primary microRNAs), based on massively parallel signature sequencing data. The third module, 'MiR¨CTar', was designed to validate thousands of miRNA¡ªtarget pairs by using parallel analysis of RNA end (PARE) data. Correspondingly, the fourth module, 'Self-reg', also used PARE data to investigate the metabolism of miRNA precursors, including precursor processing and miRNA- or miRNA*-mediated self-regulation effects on their host precursors. PmiRKB can be freely accessed at http://bis.zju.edu.cn/pmirkb/.

  PRIN (Predicted Rice Interactome Network), is the first well annotated protein interaction database for the important model plant Oryza sativa. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology. Protein-protein interactions data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), human (Homo sapiens), Escherichia coli K12 and Arabidopsis thaliana. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.

  Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides variously user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a ¡°Gene Set Analysis¡± module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/.

  OsCAS (Oryza sativa Chips Annotation System) is a comprehensive system designed to annotate the results of rice microarray experiments and analysis relationships between genes based on their expression. The aim of the platform is to facilitate the study of differently expressed genes in the microarray experiments within the framework of systems biological research. Using a user-friendly web interface, OsCAS accepts a set of genechip IDs which can be used to retrieve relavent annotations using programs selected by the user. Several public databases are integrated, including Genebank, Unigene, SwissProt, TIGR, KOME, KEGG, Gene Ontology, MirBase to cover gene information, protein features, metabolic pathways, regulatory factors in rice. OsCAS has been applied successfully to annotate large sets of genechip IDs from several rice microarray experiments and to facilitate the further analysis of varied genes.

  We developed a web-based platform to provide the web service programs for high-throughput microarry data analysis. Implement a large collection of web services focused on microarray data, that is, multiple tasks, automated analyses that are accessed programmatically rather than through manual interaction with the web server. It contains an integrated annotation system that provides various functional information of probes and genes. Several useful components are available for gene function classification, gene set enrichment analysis, co-expression discovery, pathway inference, and more flexible model establishment.