Construction of a Molecular Learning Network
Tomohiro Shirakawa and Hiroshi Sato
Department of Computer Science, National Defense Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan
Learning ability in unicellular organisms has been studied since the first half of the 20th century, but there is still no clear evidence of unicellular learning. Based on results from previous associative learning experiments using the Physarum plasmodium, a gene regulatory network model of unicellular learning was constructed. The model demonstrates that, in principle, unicellular learning can be achieved through the cooperation of several biomolecules.
-  J.W. French, “Trial and error learning in paramecium,” J. Exp. Psycol., Vol.26, pp. 609-613, 1940.
-  T. M. Hennessey, W. B. Rucker, and C. G. McDiarmid, “Classical conditioning in paramecia,” Anim. Learn Behav., Vol.7, pp. 417-423, 1979.
-  N. Gandhi, G. Ashkenasy, and E. Tannenbaum, “Associative learning in biochemical networks,” J. Theor. Biol., Vol.249, pp. 58-66, 2000.
-  C. T. Fernando, A. M. L. Liekens, L. E. H. Bingle, C. Beck, T. Lenser, D. J. Stekel, and J. E. Rowe, “Molecular circuits for associative learning in single-celled organisms,” J. R. Soc. Interface, Vol.6, pp. 463-469, 2008.
-  M. O. Magnasco, “Chemical kinetics is Turing universal,” Phys. Rev. Lett., Vol.78, pp. 1190-1193, 1997.
-  T. Nakagaki, H. Yamada, and Á. Tóth, “Maze-solving by an amoeboid organism,” Nature, Vol.407, p. 470, 2000.
-  T. Nakagaki, H. Yamada, and M. Hara, “Smart network solutions in an amoeboid organism,” Biophys. Chemist., Vol.107, pp. 1-5, 2003.
-  T. Shirakawa and Y.-P. Gunji, “Emergence of morphological order in the network formation of Physarum polycephalum,” Biophys. Chemist., Vol.128, pp. 253-260, 2007.
-  T. Saigusa, A. Tero, T. Nakagaki, and Y. Kuramoto, “Amoeba anticipate periodic events,” Phys. Rev. Lett., Vol.100, 018101, 2008.
-  T. Shirakawa, Y.-P. Gunji, and Y. Miyake, “An associative learning experiment using the plasmodium of Physarum plasmodium,” Nano Commun. Netw., Vol.2, pp. 99-105, 2011.
-  T. Lenser, T. Hinze, B. Ibrahim, and P. Dittrich, “Toward evolutionary network reconstruction tools for systems biology,” Proc. of the 5th European Conf. on Evolutionary Computation, machine learning and data mining in bioinformatics, pp. 132-142, April 2007.
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