Laboratory introduction

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    Along with the significant progress in computer performance in recent years, computational algorithms and numerical methods that have been considered within theoretical frameworks are now becoming executable. In the field of statistics, the benefits of these developments in computer performance and computational algorithms have been applied to various fields such as healthcare and economics, resulting in new statistical methods. In particular, as medical treatment has become increasingly sophisticated and complex, such as personalized medicine utilizing gene expression information, large amounts of data have been accumulated, creating opportunities to utilize statistics supported by high-performance computers and fast computing algorithms. In the era of big data, the demand for statisticians and data scientists who can analyze medical data, including genetic information, and extract medical and pharmaceutical significance is increasing rapidly, highlighting the urgent need for talent development. In response to these social demands, the Laboratory of Biostatistics not only applies existing statistical methods but also actively proposes new methods in biostatistics, computational statistics, and Bayesian statistics, conducting research aimed at the application and utilization of gene expression data and medical data.