Genome-level integration of gene functional information and its application to elucidation of gene systems

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Although a large amount of data about genes from the genomes of many organisms has been obtained, the filmdom of many genes are still uncharacterized. This was due to the facts that the information of gene functions were not systematically arranged and not easily utilized, and the method for classifying genes to the gene families of functionally-coupled groups with their sequence homologies or expression similarities. To cope with these issues, this study aims to elucidate gene systems focusing on gene interactions by developing methods for systematic extraction of clearly-characterized gene functions and systematic arrangement of the extracted functional information in genome level.The achievements of this study are:(1) More accurate inference of gene regulatory networks with Bayesian network from gene expression data by using the functional classification of Gene Ontology as well as expression similarity.(2) Mapping genes on microarrays onto the KEGG metabolic pathway database, construction of the system for analyzing the genes with their microarray data, the computational analysis of the tryptophan degradation pathway in mouse and the prediction of the existence of an alternative pathway.(3) Development of analysis pipeline called SayaMatcher for finding the transcription-factor binding sites of which number is expected as several thousands to several hundreds of thousands.(4) Construction of a DAS (Distributed Annotation System) server that makes it possible to display and browse those found binding sites and their positions on the genome.