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Author: Sosuke Ito Publisher: Springer ISBN: 981101664X Category : Science Languages : en Pages : 140
Book Description
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.
Author: Sosuke Ito Publisher: Springer ISBN: 981101664X Category : Science Languages : en Pages : 140
Book Description
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.
Author: Naoto Shiraishi Publisher: Springer Nature ISBN: 9811981868 Category : Science Languages : en Pages : 437
Book Description
This book presents the fundamentals of stochastic thermodynamics, one of the most central subjects in non-equilibrium statistical mechanics. It also explores many recent advances, e.g., in information thermodynamics, the thermodynamic uncertainty relation, and the trade-off relation between efficiency and power. The content is divided into three main parts, the first of which introduces readers to fundamental topics in stochastic thermodynamics, e.g., the basics of stochastic processes, the fluctuation theorem and its variants, information thermodynamics, and large deviation theory. In turn, parts two and three explore advanced topics such as autonomous engines (engines not controlled externally) and finite speed engines, while also explaining the key concepts from recent stochastic thermodynamics theory that are involved. To fully benefit from the book, readers only need an undergraduate-level background in statistical mechanics and quantum mechanics; no background in information theory or stochastic processes is needed. Accordingly, the book offers a valuable resource for early graduate or higher-level readers who are unfamiliar with this subject but want to keep up with the cutting-edge research in this field. In addition, the author’s vivid descriptions interspersed throughout the book will help readers grasp ‘living’ research developments and begin their own research in this field.
Author: Kiyoshi Kanazawa Publisher: Springer ISBN: 981106332X Category : Science Languages : en Pages : 231
Book Description
The author investigates athermal fluctuation from the viewpoints of statistical mechanics in this thesis. Stochastic methods are theoretically very powerful in describing fluctuation of thermodynamic quantities in small systems on the level of a single trajectory and have been recently developed on the basis of stochastic thermodynamics. This thesis proposes, for the first time, a systematic framework to describe athermal fluctuation, developing stochastic thermodynamics for non-Gaussian processes, while thermal fluctuations are mainly addressed from the viewpoint of Gaussian stochastic processes in most of the conventional studies. First, the book provides an elementary introduction to the stochastic processes and stochastic thermodynamics. The author derives a Langevin-like equation with non-Gaussian noise as a minimal stochastic model for athermal systems, and its analytical solution by developing systematic expansions is shown as the main result. Furthermore, the a uthor shows a thermodynamic framework for such non-Gaussian fluctuations, and studies some thermodynamics phenomena, i.e. heat conduction and energy pumping, which shows distinct characteristics from conventional thermodynamics. The theory introduced in the book would be a systematic foundation to describe dynamics of athermal fluctuation quantitatively and to analyze their thermodynamic properties on the basis of stochastic methods.
Author: Sajal Ray Publisher: BoD – Books on Demand ISBN: 1838800654 Category : Science Languages : en Pages : 85
Book Description
Intracellular signal transduction is an important topic of research in cell and molecular biology. It has a wide range of implications in growth, differentiation, development, animal polarity, cellular response monitoring, and many disease processes, including cancer. The functional homeostasis of a cell is assumed to be maintained by an intricate network of signaling that evolved through natural selection. This book includes chapters written in the frontier areas of research on cell signaling. Issues such as information thermodynamics, master regulation of immune tolerance, genetically encoded reporter circuits and their applications, hypoxia, and vitamin K2 mediated signaling processes are addressed and discussed by eminent researchers of the field.
Author: Matthias Dehmer Publisher: John Wiley & Sons ISBN: 352769322X Category : Medical Languages : en Pages : 296
Book Description
This latest addition to the successful Network Biology series presents current methods for determining the entropy of networks, making it the first to cover the recently established Quantitative Graph Theory. An excellent international team of editors and contributors provides an up-to-date outlook for the field, covering a broad range of graph entropy-related concepts and methods. The topics range from analyzing mathematical properties of methods right up to applying them in real-life areas. Filling a gap in the contemporary literature this is an invaluable reference for a number of disciplines, including mathematicians, computer scientists, computational biologists, and structural chemists.
Author: Sangdun Choi Publisher: Springer Science & Business Media ISBN: 1441957979 Category : Science Languages : en Pages : 900
Book Description
System Biology encompasses the knowledge from diverse fields such as Molecular Biology, Immunology, Genetics, Computational Biology, Mathematical Biology, etc. not only to address key questions that are not answerable by individual fields alone, but also to help in our understanding of the complexities of biological systems. Whole genome expression studies have provided us the means of studying the expression of thousands of genes under a particular condition and this technique had been widely used to find out the role of key macromolecules that are involved in biological signaling pathways. However, making sense of the underlying complexity is only possible if we interconnect various signaling pathways into human and computer readable network maps. These maps can then be used to classify and study individual components involved in a particular phenomenon. Apart from transcriptomics, several individual gene studies have resulted in adding to our knowledge of key components that are involved in a signaling pathway. It therefore becomes imperative to take into account of these studies also, while constructing our network maps to highlight the interconnectedness of the entire signaling pathways and the role of that particular individual protein in the pathway. This collection of articles will contain a collection of pioneering work done by scientists working in regulatory signaling networks and the use of large scale gene expression and omics data. The distinctive features of this book would be: Act a single source of information to understand the various components of different signaling network (roadmap of biochemical pathways, the nature of a molecule of interest in a particular pathway, etc.), Serve as a platform to highlight the key findings in this highly volatile and evolving field, and Provide answers to various techniques both related to microarray and cell signaling to the readers.
Author: Michal Kurzynski Publisher: Springer Science & Business Media ISBN: 9783540238881 Category : Science Languages : en Pages : 456
Book Description
Thermodynamics was created in the ?rst half of the 19th century as a theory designed to explain the functioning of heat engines converting heat into mechanical work. In the course of time, while the scope of research in this ?eld was being extended to a wider and wider class of energy transformations, thermodynamics came to be considered as a general theory of machines identi?ed with energy transducers. Imp- tant progress in biochemistry in the ?rst half of the 20th century, and in molecular biology in the second half, made it possible to think of treating even living organisms as machines, at least on the subcellular level. However, success in applying thermodynamics to elucidate the phenomenon of life has been rather mitigated. Two reasons seem to be responsible for this unsatisfactory s- uation. Nineteenth century thermodynamics dealt only with simple (homogeneous) systems in complete equilibrium. Although during the 20th century a nonequilibrium thermodynamics was developed, sta- ing with the Onsager theory of linear response and ending with the Prigogine nonlinear theory of dissipative structures, these theories still concern the originally homogeneous systems. Because living organisms are complex systems with a historically frozen spatial and functional structure, a thermodynamics of both nonequilibrium and complex s- tems is needed for their description. The ?rst goal of the present book is to formulate the foundations of such a thermodynamics.
Author: Matthias Dehmer Publisher: John Wiley & Sons ISBN: 3527339094 Category : Medical Languages : en Pages : 298
Book Description
This latest addition to the successful Network Biology series presents current methods for determining the entropy of networks, making it the first to cover the recently established Quantitative Graph Theory. An excellent international team of editors and contributors provides an up-to-date outlook for the field, covering a broad range of graph entropy-related concepts and methods. The topics range from analyzing mathematical properties of methods right up to applying them in real-life areas. Filling a gap in the contemporary literature this is an invaluable reference for a number of disciplines, including mathematicians, computer scientists, computational biologists, and structural chemists.
Author: Jonas Peters Publisher: MIT Press ISBN: 0262037319 Category : Computers Languages : en Pages : 289
Book Description
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.
Author: Sosuke Ito
Author: Sosuke Ito
Author: Naoto Shiraishi
Author: Kiyoshi Kanazawa
Author: Sajal Ray
Author: Matthias Dehmer
Author: Sangdun Choi
Author: Michal Kurzynski
Author: Matthias Dehmer
Author: Jonas Peters
Author: