Prof. Akutsu Tatsuya from Kyoto University and Assistant Prof. Takemoto Kazuhiro from Kyushu Institute of Technology visited Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences (TIB) at the invitation of Prof. Song Jiangning on March 18th, 2013.
Prof. Akutsu Tatsuya received B.Eng. and M.Eng. in Aeronautics and D.Eng. in Information Engineering from University of Tokyo, 1984, 1986 and 1989, respectively. He is a Professor in Bioinformatics Center, Institute for Chemical Research, Kyoto University. His research interests include bioinformatics and the design and analysis of algorithms. He has published more than 200 papers. And he is editor of many science magazines such as Current bioinformatics, BMC Bioinformatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
Prof. Akustu Tatsuya gave a lecture named “Analyzing Metabolic Networks Using Boolean Models”. In the lecture, he shared his mathematical models and computational methods for analyzing metabolic networks using Boolean models, where chemical compounds and reactions are modeled as OR and AND nodes, respectively.
Assistant Prof. Takemoto Kazuhiro received his doctor degree in Informatics from Kyoto University, Japan, in 2008. After that, he worked as a postdoctoral fellow at University of Tokyo, Japan, in 2009. Since 2012, he has been an assistant professor at Kyushu Institute of Technology, Japan. His research interests include theoretical and Integrative biology. Especially, he aims at integrative understanding of metabolic evolution and adaptation from a mathematical and informatics viewpoint such as computational data analysis and complex network theory.
Assistant Prof. Takemoto Kazuhiro gave a lecture named “ Current understanding of metabolic evolution and adaptation based on network theory”. He introduced the effect of chaperonin GroEL on metabolic evolution and the relationship with growth conditions such as growth temperature and metabolic network structure. He also introduced his mathematical models for the formation of metabolic networks, according to the current understanding from a perspective of metabolic networks.
