In order to understand biological information processing systems created by evolution, we focus on their (1) information theoretic optimality, (2) physico-chemical constraints, and (3) evolvability & self-reproducibility. To grasp such aspects, we are working on
In order to describe and understand information processing in living organisms, mathematical methods and theories that can capture the essence of the phenomena are necessary. While many theories and techniques have already been developed in the fields of mathematical science, physics, and engineering, they are rarely applicable to biological phenomena as they are. We need to modify, improve, and in some cases, recreate them for our purpose. Specifically, we are using the following theories in our works:
Quantitative measurement techniques for biological phenomena have made great strides in the past two decades, providing us with the data we need to investigate phenomena in detail and to test theories. We are also developing a variety of informatics methods to extract appropriate information from these quantitative data and integrate them with theories:
A close examination of biological systems let us find that even seemingly simple single cells possess breath-takingly sophisticated and efficient functions. Toward understand information processing in cells, we are working on the mathematical understanding of various phenomena in collaboration with our collaborators: