## Information Thermodynamics on Causal Networks and its Application to Biochemical Signal TransductionIn 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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### Contents

1 | |

11 | |

3 Stochastic Thermodynamics for Small System | 24 |

4 Information Thermodynamics Under Feedback Control | 41 |

5 Bayesian Networks and Causal Networks | 51 |

6 Information Thermodynamics on Causal Networks | 61 |

7 Application to Biochemical Signal Transduction | 83 |

8 Information Thermodynamics as Stochastic Thermodynamics for Small Subsystem | 98 |

9 Further Applications of Information Thermodynamics on Causal Networks | 121 |

10 Conclusions | 127 |

Appendix Curriculum Vitae | 132 |

### Other editions - View all

Information Thermodynamics on Causal Networks and its Application to ... Sosuke Ito No preview available - 2016 |

### Common terms and phrases

Application to Biochemical backward path probability backward transfer entropy Bayesian networks biochemical signal transduction causal network corresponding chain rule channel coding chemotaxis conditional mutual information conditional probability conventional thermodynamics coupled Langevin equations defined denotes detailed fluctuation theorem discuss ensemble average entropy change entropy production Example feedback control feedback loop free energy difference Gaussian given heat bath ifin information flow information thermodynamic inequality information transmission informational quantity input integral fluctuation theorem J.M. Horowitz Jarzynski equality Langevin equation law of thermodynamics Lett ligand Markov chain Maxwell’s demon Mout mutual information noisy-channel coding theorem nonequilibrium dynamics nonnegativity output Phys probability distribution Sagawa Sagawa–Ueda relation second law Seifert sensory adaptation Shannon entropy small subsystem small system Springer Science+Business Media steady-state thermodynamics stochastic relative entropy stochastic thermodynamics system X target system thermodynamic bound Thermodynamics on Causal thermodynamics with information thesis Ueda y_A+