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Information Thermodynamics on Causal Networks and its Application to Biochemical Signal Transduction

In this book the author presents a general formalism of nonequilibrium thermodynamics with complex information flows induced by interactions among multiple fluctuating systems. The author has generalized stochastic thermodynamics with information by using a graphical theory. Characterizing nonequili...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ito, Sosuke (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Springer Theses, Recognizing Outstanding Ph.D. Research,
Temas:
Acceso en línea:Texto Completo

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300 |a XIII, 133 p. 32 illus., 28 illus. in color.  |b online resource. 
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490 1 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5061 
505 0 |a Introduction to Information Thermodynamics on Causal Networks -- Review of Classical Information Theory -- Stochastic Thermodynamics for Small System -- Information Thermodynamics under Feedback Control -- Bayesian Networks and Causal Networks -- Information Thermodynamics on Causal Networks -- Application to Biochemical Signal Transduction -- Information Thermodynamics as Stochastic Thermodynamics for Small Subsystem -- Further Applications of Information Thermodynamics on Causal Networks -- Conclusions. 
520 |a In this book the author presents a general formalism of nonequilibrium thermodynamics with complex information flows induced by interactions among multiple fluctuating systems. The author has generalized stochastic thermodynamics with information by using a graphical theory. Characterizing nonequilibrium dynamics by causal networks, he has obtained a novel generalization of the second law of thermodynamics with information that is applicable to quite a broad class of stochastic dynamics such as information transfer between multiple Brownian particles, an autonomous biochemical reaction, and complex dynamics with a time-delayed feedback control. This study can produce further progress in the study of Maxwell's demon for special cases. As an application to these results, information transmission and thermodynamic dissipation in biochemical signal transduction are discussed. The findings presented here can open up a novel biophysical approach to understanding information processing in living systems. 
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