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Self-Evolvability for Biosystems

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Book cover Self-Evolvable Systems

Part of the book series: Understanding Complex Systems ((UCS))

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Abstract

The straightforwardness with which biosystems solve complex problems suggests adopting the strategies developed in nature to face evergrowing complexity for other systems.

Hypercubes for genetic code, hypercycles as a principle of self-organization, and NK-models of evolution describing genotype fitness landscape are presented.

The hierarchy of structure, function, dynamics, within spatial and temporal brain scales is characterized by the K-set models.

The correlation with differential models, entropy criteria and bio-inspired computing methods as, autonomic, and organic computing is presented.

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References

  • Ardell, D.H., Sella, G.: No accident: genetic codes freeze in error-correcting patterns of the standard genetic code. Philos. Trans. R. Soc. London B. Biol. Sci. 357(1427), 1625–1642 (2002)

    Article  Google Scholar 

  • Bauer, B., Kasinger, H.: AOSE and organic computing-how can they benefits from each other. Position paper, AOSE III. Springer (2006)

    Google Scholar 

  • Benyo, B., Biro, J.C., Benyo, Z.: Codes in the codons: Construction of a codon/amino acid periodic table and a study of the nature of specific nucleic acid-protein interactions. In: Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, pp. 2860–2863 (2004)

    Google Scholar 

  • Bertman, M.O., Jungck, J.R.: Group graph of the genetic code. The J. of Heredity 70, 379–384 (1979)

    Google Scholar 

  • Calinescu, R., Kwiatkowska, M.: CADS*: Computer-Aided Development of Self-* Systems. In: Chechik, M., Wirsing, M. (eds.) FASE 2009. LNCS, vol. 5503, pp. 421–424. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  • Engstrom, D., Kelso, J.: Coordination dynamics of the complementary nature. Gestalt Theory 30(2), 121–134 (2008)

    Google Scholar 

  • Eigen, M.: Selforganization of Matter and the Evolution of Biological Macromolecules. Naturwissenschaften 58(10), 465–523 (1971)

    Article  Google Scholar 

  • Eigen, M.: Viral Quasispecies. Scientific Am. 269, 42–49 (1993)

    Article  Google Scholar 

  • Eigen, M.: Viruses: Evolution, Propagation and Defense. Nutrition Reviews 58(2), 5–16 (2000)

    Google Scholar 

  • Eigen, M., Schuster, P.: The hypercycle a principle of natural self-organization. Springer, Berlin (1979)

    Google Scholar 

  • Eigen, M., McCaskill, J., Schuster, P.: Molecular quasispecies. J. Phys. Chem. 92, 6881–6891 (1988)

    Article  Google Scholar 

  • Findley, G.L., Findley, A.M., McGlynn, S.P.: Symmetry characteristics of the genetic code. Proc. Natl. Acad. Sci. USA 79, 7061–7065 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  • Frappat, L., Sciarrino, A., Sorba, P.: Theoretical Prevision of Physical-Chemical Properties of Amino Acids from Genetic Code (2000), http://arxiv.org/list/physics/0007034

  • Freeman, W.J.: Mass Action in the Nervous System. Academic Press, New York (1975)

    Google Scholar 

  • Freeman, W.J.: Neurodynamics. An Exploration of Mesoscopic Brain Dynamics. Spinger, London UK (2000)

    MATH  Google Scholar 

  • Freeman, W.J.: Proposed cortical “shutter” mechanism in cinematographic perception. In: Perlovsky, L., Kozma, R. (eds.) Neurodynamics of Cognition and Consciousness, pp. 11–38. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  • Grossberg, S.: The complementary brain: A unifying view of brain specialization and modularity. Trends in Cognitive Sciences 4, 233–246 (2000)

    Article  Google Scholar 

  • Freeman, W.J., Holmes, M.D.: Metastability, instability, and state transition in neocortex. Neural Networks 18(5-6), 497–504 (2005)

    Article  MATH  Google Scholar 

  • Hofmeyr, J.-H.: The biochemical factory that autonomously fabricates itself: a systems biological view of the living cell. In: Boogard, F., Bruggeman, F., Hofmeyr, J.-H., Westerhoff, H. (eds.) Systems Biology: Philosophical Foundations. Elsevier (2007)

    Google Scholar 

  • Ji, S.: Complementarism: A biology-based philosophical framework to integrate western science and eastern tao. In: Proceeding of the 16th International Congress of Psychoterapy, pp. 518–548 (1995)

    Google Scholar 

  • Jimenez-Montano, M.A.: Protein evolution drives the evolution of the genetic code and vice versa. Biosystems 54, 47–64 (1999)

    Article  Google Scholar 

  • Jimenez-Montano, M.A., de la Mora-Basanez, R., Poschel, T.: The hypercube structure of the genetic code explains conservative and non-conservative amino acid substitutions in vivo and in vitro. Biosystems 39, 117–125 (1996)

    Article  Google Scholar 

  • Jimenez-Sanchez, A.: On the Origin and Evolution of the Genetic Code. J. Mol. Evol. 41, 712–716 (1995)

    Article  Google Scholar 

  • Kauffman, S.A.: The origins of order: Self-organization and selection in evolution. Oxford University Press, New York (1993)

    Google Scholar 

  • Kauffman, S.: At home in the universe: The search for laws of self-organization and complexity. Oxford University Press, New York (1995)

    Google Scholar 

  • Kelso, J.A.S., Tognoli, E.: Toward a Complementary Neuroscience: Metastable Coordination Dynamics of the Brain. In: Murphy, N., Ellis, G.F.R., O’Connor, T. (eds.) Downward Causation and the Neurobiology of Free Will. UCS, vol. 3, pp. 103–124. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  • Kephart, J.O., Chess, D.M.: The vision of autonomic computing. IEEE Computer 36(1), 41–50 (2003)

    Article  Google Scholar 

  • Koonin, E.V., Novozhilov, A.S.: Origin and evolution of the genetic code: The universal enigma. IUBMB Life 61(2), 99–111 (2009)

    Article  Google Scholar 

  • Kuhn, H., Kuhn, C.: Diversified world: drive of life’s origin? Angew. Chem. International 42, 262–266 (2003)

    Article  Google Scholar 

  • Kuhn, H., Waser, J.: Hypothesis on the origin of genetic code. FEBS Letters 352, 259–264 (1994)

    Article  Google Scholar 

  • Moretti, A.: The Geometry of Logical Opposition. PhD. Thesis. University of Neuchâtel, Switzerland (2009)

    Google Scholar 

  • Patee, H.: The Physics and Metaphysics of Biosemiotics. Journal of Biosemiotics 1, 281–301 (2005)

    Google Scholar 

  • Pearse, E.P.J.: Canonical self-similar tilings by iterated function systems. Indiana Univ. Math. J. 56, 3151–3170 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  • Schöler, T., Müller-Schloer, C.: An Observer/Controller Architecture for Adaptive Reconfigurable Stacks. In: Beigl, M., Lukowicz, P. (eds.) ARCS 2005. LNCS, vol. 3432, pp. 139–153. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  • Schuster, P.: A testable genotype-phenotype map: Modeling evolution of RNA molecules. In: Läassig, M., Valleriani, A. (eds.) Biological Evolution and Statistical Physics, pp. 56–83. Springer, Berlin (2002)

    Google Scholar 

  • Sole, R.V., Sardanyes, J., Díez, J., Mas, A.: Information catastrophe in RNA viruses through replication thresholds. J. Theor. Biol. 240, 353–359 (2006)

    Article  Google Scholar 

  • Sterritt, R., Hinchey, M.: Autonomic Computing – Panacea or Poppycock? In: The 12th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, pp. 535–539 (2005)

    Google Scholar 

  • Taylor, W.R.: The classification of amino acid conservation. J. Theor. Biol. 119, 205–218 (1986)

    Article  Google Scholar 

  • Trumler, W., Bagci, F., Petzold, J., Ungerer, T.: Towards an organic middleware for the smart dooplate project. GI Jahrestagung (2), 626–630 (2004)

    Google Scholar 

  • Von Neumann, J.: Theory of Self-Reproducing Automata. University of Illinois Press, Urbana (1966)

    Google Scholar 

  • Wilhelm, T., Nikolajewa, S.L.: A new classification schema of the genetic code. J. Mol. Evol. 59, 598–605 (2004)

    Article  Google Scholar 

  • Wolynes, P., Onuchic, J.N., Thirumalai, D.: Navigating the folding routes. Science 267, 1619–1620 (1995)

    Article  Google Scholar 

  • Würtz, R.P. (ed.): Organic Computing: Series: Understanding Complex Systems. Springer (2008)

    Google Scholar 

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Authors and Affiliations

  1. Polystochastic, Pitfield blvd. St. Laurent 3205, H4S 1H3, Montreal, Canada

    Octavian Iordache

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  1. Octavian Iordache
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Correspondence to Octavian Iordache .

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Iordache, O. (2012). Self-Evolvability for Biosystems. In: Self-Evolvable Systems. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28882-1_6

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