Laboratories for Mathematics, Lifesciences, and Informatics

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  • 1 (2007-04-20 (金) 17:48:10)
  • 2 (2007-04-28 (土) 17:34:49)
  • 3 (2007-07-08 (日) 19:38:43)
  • 4 (2010-09-06 (月) 10:17:29)
  • 5 (2010-09-08 (水) 09:42:56)
  • 6 (2010-12-15 (水) 17:07:46)
  • 7 (2012-05-30 (水) 17:24:02)
  • 8 (2013-07-09 (火) 11:07:10)
  • 9 (2013-07-18 (木) 11:16:03)
  • 10 (2013-12-06 (金) 09:33:33)
  • 11 (2013-12-06 (金) 18:06:32)
  • 12 (2014-01-29 (水) 10:53:13)
  • 13 (2015-02-26 (木) 15:17:45)
  • 14 (2016-02-09 (火) 10:39:43)
  • 15 (2016-03-02 (水) 20:24:38)
  • 16 (2016-03-04 (金) 15:53:29)
  • 17 (2016-05-26 (木) 15:40:09)
  • 18 (2016-07-13 (水) 09:28:08)
  • 19 (2016-08-29 (月) 17:09:51)
  • 20 (2016-10-14 (金) 11:19:48)
  • 21 (2016-11-07 (月) 13:05:45)
  • 22 (2017-01-18 (水) 10:37:13)
  • 23 (2017-02-01 (水) 17:52:42)
  • 24 (2017-03-31 (金) 13:18:36)
  • 25 (2017-04-11 (火) 08:32:14)

_ Neuroscience and Biological Information Processing

Our research on neuroscience aims at understanding information processing and various behaviors in the brain. For instance, we have considered a relationship between neurophysiologic properties and neuronal functions through mathematical modeling of a neuron and neural networks [1,2]. We have derived a theoretical framework for an optimal learning rule in neuronal systems from the viewpoint of information theory [3]. Mathematical analysis of neuron models is also included in our research interests [4]. Moreover, we have been analyzing real data of neuronal spikes [5] and implementing analog devices based on neuronal properties for realizing a novel computation scheme.

1. K. Morita, K. Tsumoto, and K. Aihara, Biophys. J., Vol.90, pp.1925-1938 (2006).
2. Y. Katori, N. Masuda, and K. Aihara, Neural Networks, Vol.19, pp.1463-1466 (2006).
3. T. Toyoizumi, K. Aihara, and S. Amari, Phys. Rev. Lett., Vol.97, 098102 (2006).
4. K. Tsumoto, H. Kitajima, T. Yoshinaga, K. Aihara, and H. Kawakami, Neurocomput., Vol.69, pp.293-316 (2006).
5. K. Fujiwara, H. Fujiwara, M. Tsukada, and K. Aihara, Biosystems, in press (2007).

_ Nonlinear Dynamical Systems and its Applications

The aim of our research on nonlinear science is to understand the essence of complex behaviors through analyses of various complex nonlinear phenomena in biological, physical, and engineering systems. Putting the focus on nonlinearity, we investigate how highly complex phenomena arise in a simple nonlinear system and how self-organization takes place in a chaotic system, by developing the methods for bifurcation analysis, time series analysis, and statistical analysis [1-5]. Application studies include information processing based on nonlinear dynamics, information extraction from biological data, and deterministic chaos in wind.

1. H. Suetani, Y. Iba, and K. Aihara, J. Phys. A, Vol.39, pp.10723―10742 (2006).
2. H. Ando and K. Aihara, Phys. Rev. E, Vol.74, 066205 (2006).
3. G. Tanaka, B. Ibarz, M.A.F. Sanjuan, and K. Aihara, Chaos, Vol.16, 013113 (2006).
4. Y. Hirata, H. Suzuki, and K. Aihara, Phys. Rev. E, Vol.74, 026202 (2006).
5. N. Masuda, G. Jakimoski, K. Aihara, and L. Kocarev, IEEE Trans. Circ. Syst. I, Vol.53, pp.1341-1352 (2006).

_ Mathematical Modeling of Biochemical Systems

We study nonlinear dynamics in biochemical reactions in the cell in order to understand collective activities in the ensembles of cells. We have been studied the mechanism of biological rhythms by constructing a mathematical model of genome-proteome networks and attempted to propose a method to design artificial gene networks [1-8].

1. L. Chen, R. Wang, C. Li, and K. Aihara, Modeling Biomolecular Networks in Cells: Structures and Dynamics?, Springer (2010).
2. D. Battogtokh, K. Aihara, and J. J. Tyson, Phys. Rev. Lett., Vol.96, 148102 (2006).
3. Y. Morishita, T. J. Kobayashi, and K. Aihara, Biophys. J., Vol.91, pp.2072-2081 (2006).
4. G. Kurosawa, K. Aihara, and Y. Iwasa, Biophys. J., Vol.91, pp.2015-2023 (2006).
5. C. Li, L. Chen, and K. Aihara, Physical Biology, Vol.3, pp.37-44 (2006).
6. C. Li, L. Chen, and K. Aihara, IEEE Trans. CAS-I, Vol.53, pp.2451-2458 (2006).
7. C. Li, L. Chen, and K. Aihara, PLoS Comput. Biol., Vol.2, e103 (2006).
8. R. Wang, L. Chen, and K. Aihara, J. Theor. Biol., Vol.242, pp.454-463 (2006).

_ Mathematical Modeling of Diseases

We have been studied mathematical modeling of modern diseases that should be addressed emergently. Especially, we aim at understanding the essential mechanism and the origin of a disease and proposing a possible effective approach to avoid or treat the disease. We have discussed the efficacy of intermittent hormone suppression therapy for prostate cancer [1]. We have also carried out modeling of infection disease [2,3] and proposed a simulation system for analysis of the infection spread in the society.

1. A. Miyamura, G. Tanaka, T. Takeuchi, and K. Aihara, METR, University of Tokyo, 2006-32 (2006).
2. K. Ohtsuka, N. Konno, N. Masuda, and K. Aihara, Int. J. Bifurcation and Chaos, Vol.16, pp.3687-3693 (2006).
3. N. Sugimine, N. Masuda, N. Konno, and K. Aihara, Mathematical Biosciences, in press (2007).