Since JBIC was established in July 2000, we have focused on the structural and
functional analysis of proteins and database-related projects. Although genetic
research was initially the main emphasis, we have expanded the scope of our research
to include functional RNA, translational research (TR) and iPS cells.
We have successfully completed these projects in close cooperation with industry, academia and government, and obtained various findings and research results as follows.
Development of research tools, and enhancement of their precision
Supersensitive protein–protein interaction analysis system
World-class analysis capability utilizing electron microscope, NMR, mass spectrometer and microarray
Significant improvement in performance of an in silico simulation system and enhancement of its precision and speed
myPresto (Medicinally Yielding PRotein Engineering SimulaTOr), high-precision molecular simulation programs
Construction of Natural products library containing more than 300,000 samplesThe natural compounds produced by a microbe are very useful as a new drug candidate compound.
Construction of Human proteome expression resource (HUPEX)Full-length cDNA clones are essential experimental tools for functional analysis of human genes and proteins. We have constructed over 40,000 human Gateway entry clones from full-length cDNAs which cover approximately 80% of all human genes. This set is the Human Proteome Expression Resource (HUPEX) and biological data for these clones are presented in the Human Gene and Protein Database (HGPD)
Glis 1: Discovery of a new high-efficiency inductive transcription factor of iPS cells
In the study conducted in collaboration with Prof. Shinya Yamanaka of Kyoto University, Glis 1 was found in the full-length cDNA library as a new transcription factor to induce iPS cells with higher efficiency and improved safety. There are high hopes that this result will contribute to clinical applications in the future.
Development of PaGE-OM (Phenotype and Genotype-Object Model)
We developed a method for the genotype-phenotype data description format, called PaGE-OM, which describes the relation between individual DNA genotypes and phenotypes such as disease or drug susceptibility, which was approved and adopted as an international standard.
We encourage industry and academia to use the findings of our projects.