Although a huge amount of mammalian genomic data does become publicly available, …

• Abstract
• Abstract
• Introduction
• Systems and Method
• Implementation
• Results and Discussion
• Conclusion
• Miscellaneous
• References
• Table 1
• Table 2
• Table 3
• Figures

When a complex biological event is to be explored, a data-drivenapproach is widely accepted as a powerful alternative to a conventionalhypothesis-driven one (Smalheiser, 2002). However, the data-drivenapproach cannot be achieved without high-quality genomic data.In this regard, DNA microarray technology has opened the wayto the comprehensive collection of large amounts of data regardinggenome-wide gene expression profiles, and is now recognizedas a standard tool for the characterization of biological systemsat the mRNA level. The description of biological systems withtens of thousands of different mRNA expression levels is highlysensitive to the state of those systems, and has enabled usto discover a number of mRNA biomarkers for various biologicalevents (Abbas et al., 2005; Komor et al., 2005; Su et al., 2004;Zheng et al., 2006). However, the discovery of such biomarkersdoes not necessarily address the molecular mechanisms underlyingthe observed biological events. This is mainly because mRNAlevels do not always have direct relevance to biological phenomenain general; mRNA is a template of protein synthesis and is nota functional element in itself in most cases. In this respect,protein profiles must have a greater relevance to biologicalevents than mRNA profiles because proteins govern them directly.Thus, genome-wide characterization of the biological systemat the protein level is widely considered to be the next goalto achieve, although this in itself is challenging due to technologicallimitations faced at present (Cutler, 2003). The low availabilityof quantitative proteomic data is one of bottlenecks when analyzinga biological system from an ‘omics’ viewpoint. Toaddress this problem, we have recently reported an approachfor generating quantitative proteomic maps based on two-dimensionalgel electrophoresis (2-DE) and have attempted to expand theprotein profiling data (Kimura et al., 2006). As more mRNA and protein profile data has accumulated, the demandfor a cross-referencing database has increased significantly.We have therefore developed a web-based platform for sharingspecialized immune cell mRNA and protein profile data. For thisstudy, all of the profile data was newly obtained followingwell-controlled protocols. Affymetrix GeneChip DNA microarraytechnology was utilized for obtaining mRNA profiles and 2-DEfor quantitative protein profiling. In order to integrate the‘omics’ data obtained for various immune cells,we annotated each sample with controlled vocabularies and implementeda relational database that included the quantitative mRNA andprotein profiling data. The Reference genomics Database of ImmuneCells (RefDIC) offers a web-based query interface and user-friendlydata visualizing facilities, and also allows all of the rawdata to be downloaded. RefDIC could serve as a solid referencefor the transcriptome and proteome of immune cells, and hencecould greatly facilitate the identification of immunologicallyimportant genes and proteins that are involved in various immuneresponses, through cross-referencing quantitative mRNA and proteinprofiling data.