Biological Knowledge Based on Genome Information

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While the complete genome sequences of a number of organisms, as well as the raft sequences of the human genome, have already been determined, functional properties are not well characterized for roughly a half of the genes in each genome. This project aimed at developing bioinformatics technologies for understanding hihgher order functional meanings and utilities of the cell or the organism from its genome information. Specifically, (1) we developed a reference database named KEGG, which contains current knowledge on protein interaction networks such as metabolic pathways, various regulatory pathways, and molecular complexes. We performed prediction of protein networks and associated cellular functions for the genomes of over 50 species. (2) We developed information technology to extract knowledge on protein names and protein-protein interactions from the text in scientific literature. (3) We developed information technology to analyze gene expression profile data, such as for detecting coexpression clusters and for predicting gene regulatory networks. (4) We continued to develop mutation database for disease related genes. The project has been instrumental in further developing the GenomeNet database service as the informatics infrastructure for biomedical research in Japan and in nurturing the bioinformatics research community by regularly organizing workshops and tutorials. The basic research results, as well as the practical database products such as KEGG, are freely made available at the GenomeNet (http://www.genome.ad.jp).