Dr. Kazuhiro Takemoto

Department of Bioscience and Bioinformatics

Kyushu Institute of Technology, Japan

Associate Professor

Email: takemoto@bio.kyutech.ac.jp

Qualifications

2008 Ph.D., Graduate School of Informatics, Kyoto University

2006 M.Sc., Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology

2004 B.Sc., Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology

Publications (selected)

1. Takemoto, K. and Kawakami, Y. The proportion of genes in a functional category is linked to mass-specific metabolic rate and lifespan. Scientific Reports 5, 10008 (2015).
2. Takemoto, K. Metabolic networks are almost nonfractal: A comprehensive evaluation. Physical Review E 90, 022802 (2014).
3. Feng, W. and Takemoto, K. Heterogeneity in ecological mutualistic networks dominantly determines community stability. Scientific Reports 4, 5912 (2014).
4. Takemoto, K., Kanamaru, S. and Feng, W. Climatic seasonality may affect ecological network structure: Food webs and mutualistic networks. Biosystems 121, 29-37 (2014).
5. Takemoto, K. and Yoshitake, I. Limited influence of oxygen on the evolution of chemical diversity in metabolic networks. Metabolites 3, 979-992 (2013).
6. Takemoto, K., Tamura, T. and Akutsu, T. Theoretical estimation of metabolic network robustness against multiple reaction knockouts using branching process approximation. Physica A 392, 5525-5535 (2013).
7. Takemoto, K. and Kihara, K. Modular organization of cancer signaling networks is associated with patient survivability. Biosystems 113, 149-154 (2013).
8. Takemoto, K. Does habitat variability really promote metabolic network modularity? PLoS ONE 8, e61348 (2013).
9. Takemoto, K. Metabolic network modularity arising from simple growth processes. Physical Review E 86, 036107 (2012).
10. Takemoto, K., Tamura, T., Cong, Y., Ching, W.-K., Vert, J.-P. and Akutsu, T. Analysis of the impact degree distribution in metabolic networks using branching process approximation. Physica A 391, 379-387 (2012).
11. Takemoto, K. Current understanding of the formation and adaptation of metabolic systems based on network theory. Metabolites 2, 429-457 (2012).
12. Takemoto, K. and Oosawa, C. Modeling for evolving biological networks. In Statistical and Machine Learning Approaches for Network Analysis (eds. Dehmer, M. and Basak, S.C.), John Wiley & Sons (2012).
13. Takemoto, K. and Borjigin, S. Metabolic network modularity in Archaea depends on growth conditions. PLoS ONE 6, e25874 (2011).
14. Takemoto, K., Niwa, T. and Taguchi, H. Difference in the distribution pattern of substrate enzymes in the metabolic network of Escherichia coli, according to chaperonin requirement. BMC Systems Biology 5, 98 (2011).
15. Takemoto, K. and Arita, M. Nested structure acquired through simple evolutionary process. Journal of Theoretical Biology 264, 782-786 (2010).
16. Takemoto, K. Global architecture of metabolite distributions across species and its formation mechanisms. Biosystems 100, 8-13 (2010).
17. Takemoto, K. and Akutsu, T. Origin of structural difference in metabolic networks with respect to temperature. BMC Systems Biology 2, 82 (2008).
18. Takemoto, K., Nacher, J.C. and Akutsu, T. Correlation between structure and temperature in prokaryotic metabolic networks. BMC Bioinformatics 8, 303 (2007).
19. Takemoto, K. and Oosawa, C. Modeling for evolving biological networks with scale-free connectivity, hierarchical modularity, and disassortativity. Mathematical Biosciences 208, 454-468 (2007).
20. Takemoto, K. and Oosawa, C. Evolving networks by merging cliques. Physical Review E 72, 046116 (2005).

PersonalWebsite: http://sites.google.com/site/kztakemoto