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008 170213s2015 ne | s |||| 0|eng d
020 _a9789401798198
_9978-94-017-9819-8
024 7 _a10.1007/978-94-017-9819-8
_2doi
035 _ato000562657
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQD431-431.7
072 7 _aPSBC
_2bicssc
072 7 _aSCI007000
_2bisacsh
082 0 4 _a572.6
_223
100 1 _aAsano, Masanari.
_eauthor.
_9470939
245 1 0 _aQuantum Adaptivity in Biology: From Genetics to Cognition
_helectronic resource
_cby Masanari Asano, Andrei Khrennikov, Masanori Ohya, Yoshiharu Tanaka, Ichiro Yamato.
260 _aDordrecht :
_bSpringer Netherlands :
_bImprint: Springer,
_c2015.
300 _aXX, 173 p. 27 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aPreface.- Introduction -- Fundamentals of classical probability and quantum probability Theory -- Fundamentals of molecular biology.-  Adaptive dynamics and general approach to non-Kolmogorov probability theory.- Application of adaptive dynamics to Biology -- Application to decision making theory and cognitive science -- Operational Approach to Modern Theory of Evolution.- Epigenetic Evolution and Theory of Open Quantum Systems -- Foundational Problems of Quantum Mechanics -- Decision and Intention Operators as Generalized Quantum Observables.
520 _aThis book examines information processing performed by bio-systems at all scales: from genomes, cells, and proteins to cognitive and even social systems. It introduces a theoretical/conceptual principle based on quantum information and non-Kolmogorov probability theory to explain information processing phenomena in biology as a whole. The book begins with an introduction followed by two chapters devoted to fundamentals, one covering classical and quantum probability, which also contains a brief introduction to quantum formalism, and another on an information approach to molecular biology, genetics, and epigenetics. It then goes on to examine adaptive dynamics, including applications to biology, and non-Kolmogorov probability theory. Next, the book discusses the possibility to apply the quantum formalism to model biological evolution, especially at the cellular level: genetic and epigenetic evolutions. It also presents a model of the epigenetic cellular evolution based on the mathematical formalism of open quantum systems. The last two chapters of the book explore foundational problems of quantum mechanics and demonstrate the power of usage of positive operator valued measures (POVMs) in biological science. This book will appeal to a diverse group of readers including experts in biology, cognitive science, decision making, sociology, psychology, and physics; mathematicians working on problems of quantum probability and information; and researchers in quantum foundations.
650 0 _aLife Sciences.
_9295653
650 0 _aBehavioral Sciences.
_9455841
650 0 _aProteins.
_9461362
650 0 _aNeural networks (Computer science).
_9372701
650 0 _aProbabilities.
_9295556
650 0 _aQuantum Physics.
_9304888
650 0 _aBiophysics.
_9459674
650 0 _aBiological physics.
_9460202
650 1 4 _aLife Sciences.
_9295653
650 2 4 _aProtein Science.
_9410551
650 2 4 _aBiophysics and Biological Physics.
_9410468
650 2 4 _aProbability Theory and Stochastic Processes.
_9303734
650 2 4 _aBehavioral Sciences.
_9455841
650 2 4 _aQuantum Physics.
_9304888
650 2 4 _aMathematical Models of Cognitive Processes and Neural Networks.
_9413655
700 1 _aKhrennikov, Andrei.
_eauthor.
_9470940
700 1 _aOhya, Masanori.
_eauthor.
_9470941
700 1 _aTanaka, Yoshiharu.
_eauthor.
_9470942
700 1 _aYamato, Ichiro.
_eauthor.
_9470943
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
856 4 0 _uhttp://dx.doi.org/10.1007/978-94-017-9819-8
912 _aZDB-2-SBL
999 _c417348