Our research is aiming to make distinct contributions in both methodological and practical aspects of the present-day "Big Data" science, especially biomedical science. We analyze diverse and heterogeneous types of genomic and biomedical data to find new knowledge and insights. Utilizing supercomputing resources, informatics and statistics approaches are used for the analysis. Over a decade ago, the representative human genome was sequenced relying on the efforts of many researchers worldwide and cost of more than one billion dollars. Nowadays, however, personal genomes are being sequenced more easily and faster at lower cost. This situation means that novel methodological advances are absolutely required for the integration and analysis of individual genomes, omics, and biomedical information (e.g., physiological and clinical information). On the basis of this view, faculty staffs majoring in bioinformatics, statistical mathematics, population genetics, and molecular evolutionary biology are actively conducting research in our laboratory. Graduate students can conduct their research in advanced computer science, massive data analysis, statistical modeling, algorithm/software development, etc., with our laboratory members. We turn out individuals who can solve flood of biomedical information from the data-driven science point of view.