Genome Scale Prediction of Enzyme Genes Utilizing the Knowledge of Metabolic Interactions

Hidemasa Bono (bono@kuicr.kyoto-u.ac.jp)
Hiroyuki Ogata (ogata@kuicr.kyoto-u.ac.jp)
Susumu Goto (goto@kuicr.kyoto-u.ac.jp)
Minoru Kanehisa (kanehisa@kuicr.kyoto-u.ac.jp)

Institute for Chemical Research, Kyoto University
Gokasho, Uji, Kyoto 611, Japan


Abstract

Thanks to various genome projects, genome scale protein sequence data have become available. Predicting gene locations and gene functions by computational methods is a very important stage in the genome project. We are developing a systematic method of predicting enzyme genes for an organism with its entire genomic sequence known, utilizing the knowledge organized in KEGG (Kyoto Encyclopedia of Genes and Genomes). The system can also help reconsider the functional assignments of the genomes previously determined and the gene catalog can be fixed accordingly.