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140908 ||| eng |
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|a 9783319084886
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| 100 |
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|a Bressloff, Paul C.
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| 245 |
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|a Stochastic Processes in Cell Biology
|h Elektronische Ressource
|c by Paul C. Bressloff
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| 250 |
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|a 1st ed. 2014
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2014, 2014
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| 300 |
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|a XVII, 679 p. 206 illus., 90 illus. in color
|b online resource
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| 505 |
0 |
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|a Introduction -- Diffusion in Cells: Random walks and Brownian Motion -- Stochastic Ion Channels -- Polymers and Molecular Motors -- Sensing the Environment: Adaptation and Amplification in Cells -- Stochastic Gene Expression and Regulatory Networks -- Transport Processes in Cells -- Self-Organization in Cells I: Active Processes -- Self-Organization in Cells II: Reaction-Diffusion Models -- The WKB Method and Large Deviation Theory -- Probability Theory and Martingales
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| 653 |
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|a Cell biology
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| 653 |
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|a Biomathematics
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| 653 |
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|a Mathematical and Computational Biology
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| 653 |
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|a Cell Biology
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| 653 |
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|a Probability Theory and Stochastic Processes
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| 653 |
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|a Probabilities
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Interdisciplinary Applied Mathematics
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-08488-6?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 570.285
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| 520 |
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|a This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods. This text is primarily aimed at graduate students and researchers working in mathematical biology and applied mathematicians interested in stochastic modeling. Applied probabilists and theoretical physicists should also find it of interest. It assumes no prior background in statistical physics and introduces concepts in stochastic processes via motivating biological applications. The book is highly illustrated and contains a large number of examples and exercises that further develop the models and ideas in the body of the text. It is based on a course that the author has taught at the University of Utah for many years
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