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  • 1.
    Asano, Masanari
    et al.
    Natl Inst Technol, Japan.
    Basieva, Irina
    Linnaeus University, Faculty of Technology, Department of Mathematics.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics. Natl Res Univ Informat Technol Mech & Opt ITMO, Russia.
    Yamato, Ichiro
    Tokyo Univ Sci, Japan.
    A model of differentiation in quantum bioinformatics2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 130, p. 88-98Article, review/survey (Refereed)
    Abstract [en]

    Differentiation is a universal process found in various phenomena of nature. As seen in the example of cell differentiation, the creation diversity on individual's character is caused by environmental interactions. In this paper, we try to explain its mechanism, which has been discussed mainly in Biology, by using the formalism of quantum physics. Our approach known as quantum bioinformatics shows that the temporal change of statistical state called decoherence fits to describe non-local phenomena like differentiation. (C) 2017 Elsevier Ltd. All rights reserved.

  • 2.
    Baladron, Carlos
    et al.
    Univ Valladolid, Spain.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics. Natl Res Univ Informat Technol Mech & Opt ITMO, Russia.
    Outline of a unified Darwinian evolutionary theory for physical and biological systems2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 130, p. 80-87Article, review/survey (Refereed)
    Abstract [en]

    The scheme of a unified Darwinian evolutionary theory for physical and biological systems is described. Every physical system is methodologically endowed with a classical information processor, which turns every system into an agent being also susceptible to evolution. Biological systems retain this structure as natural extensions of physical systems from which they are built up. Optimization of information flows turns out to be the key element to study the possible emergence of quantum behavior and the unified Darwinian description of physical and biological systems. The Darwinian natural selection scheme is completed by the Lamarckian component in the form of the anticipation of states of surrounding biophysical systems. (C) 2017 Elsevier Ltd. All rights reserved.

  • 3.
    Baladron, Carlos
    et al.
    Univ Valladolid, Spain.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics. Natl Res Univ Informat Technol Mech & Opt, Russia.
    Yamato, Ichiro
    Tokyo Univ Sci, Japan.;Chiba Univ, Japan.
    Editorial2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 130, p. 1-1Article in journal (Other academic)
  • 4.
    Khrennikov, Andrei
    et al.
    Linnaeus University, Faculty of Technology, Department of Mathematics.
    Yurova, Ekaterina
    Linnaeus University, Faculty of Technology, Department of Mathematics.
    Automaton model of protein: Dynamics of conformational and functional states2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 130, no A, p. 2-14Article in journal (Refereed)
    Abstract [en]

    In this conceptual paper we propose to explore the analogy between ontic/epistemic description of quantum phenomena and interrelation between dynamics of conformational and functional states of proteins. Another new idea is to apply theory of automata to model the latter dynamics. In our model protein's behavior is modeled with the aid of two dynamical systems, ontic and epistemic, which describe evolution of conformational and functional states of proteins, respectively. The epistemic automaton is constructed from the ontic automaton on the basis of functional (observational) equivalence relation on the space of ontic states. This reminds a few approaches to emergent quantum mechanics in which a quantum (epistemic) state is treated as representing a class of prequantum (ontic) states. This approach does not match to the standard protein structure-function paradigm. However, it is perfect for modeling of behavior of intrinsically disordered proteins. Mathematically space of protein's ontic states (conformational states) is modeled with the aid of p-adic numbers or more general ultrametric spaces encoding the internal hierarchical structure of proteins. Connection with theory of p-adic dynamical systems is briefly discussed.

  • 5.
    Melkikh, Alexey V.
    et al.
    Ural Fed Univ, Russia.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics. Natl Res Univ Informat Technol Mech & Opt ITMO, Russia.
    Molecular recognition of the environment and mechanisms of the origin of species in quantum-like modeling of evolution2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 130, p. 61-79Article, review/survey (Refereed)
    Abstract [en]

    A review of the mechanisms of speciation is performed. The mechanisms of the evolution of species, taking into account the feedback of the state of the environment and mechanisms of the emergence of complexity, are considered. It is shown that these mechanisms, at the molecular level, cannot work steadily in terms of classical mechanics. Quantum mechanisms of changes in the genome, based on the long-range interaction potential between biologically important molecules, are proposed as one of possible explanation. Different variants of interactions of the organism and environment based on molecular recognition and leading to new species origins are considered. Experiments to verify the model are proposed. This bio-physical study is completed by the general operational model of based on quantum information theory. The latter is applied to model of epigenetic evolution. We briefly present the basics of the quantum-like approach to modeling of bio-informational processes. This approach is illustrated by the quantum-like model of epigenetic evolution. (C) 2017 Elsevier Ltd. All rights reserved.

  • 6.
    Melkikh, Alexey V.
    et al.
    Ural Fed Univ, Russia.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics.
    Nontrivial quantum and quantum-like effects in biosystems: Unsolved questions and paradoxes2015In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 119, no 2, p. 137-161Article, review/survey (Refereed)
    Abstract [en]

    Non-trivial quantum effects in biological systems are analyzed. Some unresolved issues and paradoxes related to quantum effects (Levinthal's paradox, the paradox of speed, and mechanisms of evolution) are addressed. It is concluded that the existence of non-trivial quantum effects is necessary for the functioning of living systems. In particular, it is demonstrated that classical mechanics cannot explain the stable work of the cell and any over-cell structures. The need for quantum effects is generated also by combinatorial problems of evolution. Their solution requires a priori information about the states of the evolving system, but within the framework of the classical theory it is not possible to explain mechanisms of its storage consistently. We also present essentials of so called quantum-like paradigm: sufficiently complex bio-systems process information by violating the laws of classical probability and information theory. Therefore the mathematical apparatus of quantum theory may have fruitful applications to describe behavior of bio-systems: from cells to brains, ecosystems and social systems. In quantum-like information biology it is not presumed that quantum information bio-processing is resulted from quantum physical processes in living organisms. Special experiments to test the role of quantum mechanics in living systems are suggested. This requires a detailed study of living systems on the level of individual atoms and molecules. Such monitoring of living systems in vivo can allow the identification of the real potentials of interaction between biologically important molecules. (C) 2015 Elsevier Ltd. All rights reserved.

  • 7.
    Melkikh, Alexey V.
    et al.
    Ural Federal University, Russia.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics.
    Quantum-like model of partially directed evolution2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 125, p. 36-51Article in journal (Refereed)
    Abstract [en]

    The background of this study is that models of the evolution of living systems are based mainly on the evolution of replicators and cannot explain many of the properties of biological systems such as the existence of the sexes, molecular exaptation and others. The purpose of this study is to build a complete model of the evolution of organisms based on a combination of quantum-like models and models based on partial directivity of evolution. We also used optimal control theory for evolution modeling. We found that partial directivity of evolution is necessary for the explanation of the properties of an evolving system such as the stability of evolutionary strategies, aging and death, the presence of the sexes. The proposed model represents a systems approach to the evolution of species and will facilitate the understanding of the evolution and biology as a whole.

  • 8.
    Yamato, Ichiro
    et al.
    Tokyo Univ Sci, Japan;Chiba Univ, Japan.
    Murata, Takeshi
    Chiba Univ, Japan;JST, Japan.
    Khrennikov, Andrei
    Linnaeus University, Faculty of Technology, Department of Mathematics. Natl Res Univ Informat Technol Mech & Opt ITMO, Russia.
    Energy and information flows in biological systems: Bioenergy transduction of V-1-ATPase rotary motor and dynamics of thermodynamic entropy in information flows2017In: Progress in Biophysics and Molecular Biology, ISSN 0079-6107, E-ISSN 1873-1732, Vol. 130, p. 33-38Article, review/survey (Refereed)
    Abstract [en]

    We classify research fields in biology with respect to flows of materials, energy, and information. We investigate energy transducing mechanisms in biology, using as a representative the typical molecular rotary motor Vi-ATPase from a bacterium Enterococcus hirae. The structures of several intermediates of the rotary motor are described and the molecular mechanism of the motor converting chemical energy into mechanical energy is discussed. Comments and considerations on the information flows in biology, especially on the thermodynamic entropy in quantum physical and biological systems, are presented in section 3 in a biologist friendly manner. (C) 2017 Elsevier Ltd. All rights reserved.

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