2000 Fiscal Year Final Research Report Summary
Biological Knowledge Based on Genome Information
| Project/Area Number |
08283103
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas (A)
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| Allocation Type | Single-year Grants |
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| Research Institution | KYOTO UNIVERSITY |
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Principal Investigator |
KANEHISA Minoru Institute for Chemical Research, Professor, 化学研究所, 教授 (70183275)
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| Co-Investigator(Kenkyū-buntansha) |
KUHARA Satoru Kyushu University, Graduate School of Genetic Resources Technology, Professor, 大学院・農学研究院, 教授 (00153320)
MIYANO Satoru University of Tokyo. Institute of Medical Science, Professor, 医科学研究所, 教授 (50128104)
TAKAGI Toshihisa University of Tokyo, Institute of Medical Seience, Professor, 医科学研究所, 教授 (30110836)
AKUTSU Tatsuya University of Tokyo, Institute of Medical Science, Associate Professor, 医科学研究所, 助教授 (90261859)
MATSUDA Hideo Osaka University, Graduate School of Engineering Science, Associate Professor, 大学院・基礎工学研究科, 助教授 (50183950)
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| Project Period (FY) |
1996 – 2000
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| Keywords | Genome analysis / Gene function prediction / Protein structure prediction / Database / Network / Molecular interactions / Pathway / Genetic diseases |
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| Research Abstract |
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).
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