Associate Professor
Department of Bioscience and Bioinformatics
Kyushu Institute of Technology
九州工業大学 生命化学情報工学科 准教授

Kawazu 680-4, Iizuka, Fukuoka 820-8502, Japan
〒820-8502 福岡県飯塚市川津680-4
Phone: +81-948-29-7822
Fax: +81-948-29-7801
E-mail: takemoto[AT]
Twitter: kztakemoto


I aim for integrated understanding of bio-ecosystems from a viewpoint of network science, computational and integrative biology. In particular, I focus on metabolic networks. Living organisms are adapted to their environment by changing their metabolic networks, and they compose ecosystems via their metabolic networks. Metabolic networks are useful for the evaluation, design, and control of bio-ecosystems. I establish novel theoretical frameworks for analyzing bio-ecosystems using a large amount of biological and environmental data, and apply them to environmental and medical fields. In particular, I focus on the development of computational methods for reverse ecology and their applications.


What's New

  • New paper out. Our network analysis of brain diffusion tensor images indicates that the brain regions related to neuroticism exist in various regions, and that the neuroticism trait is likely formed as a result of interactions among these regions. 2018/11/8
  • New paper out. Our global-scale network analysis indicates that mutualistic ecosystems that exist despite extensive environmental changes (human impact and warming velocity) exhibit higher network resilience. 2018/9/12
  • New paper out. Our global-scale analysis revealed how ocean environments contribute to predator–prey body-size relationships in marine food webs. 2018/7/18
  • New paper out. Network science meets toxicology and human health. 2018/5/30
  • New paper out. We developed a much faster MAPLE system for evaluating potential functionome of genomes and metagenomes. 2018/5/24
  • Our article on ecological networks is out. This article is included in Encyclopedia of Bioinformatics and Computational Biology. 2018/3/30
  • New paper out. Network analysis of protein contact maps improves inferring enzyme catalytic sites. 2018/2/6
  • New paper out. Large-scale aggregation analysis of eukaryotic proteins reveals an involvement of intrinsically disordered regions in protein folding. 2018/1/22
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