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170802 ||| eng |
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|a 9783319612959
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| 100 |
1 |
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|a Rudnicki, Ryszard
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| 245 |
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|a Piecewise Deterministic Processes in Biological Models
|h Elektronische Ressource
|c by Ryszard Rudnicki, Marta Tyran-Kamińska
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a IX, 169 p. 10 illus
|b online resource
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| 505 |
0 |
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|a 1 Biological Models -- 2 Markov Processes -- 3 Operator Semigroups -- 4 Stochastic Semigroups -- 5 Asymptotic Properties of Stochastic Semigroups — General Results -- 6 Asymptotic Properties of Stochastic Semigroups — Applications
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| 653 |
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|a Complex Systems
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| 653 |
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|a Bioinformatics
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| 653 |
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|a Computational and Systems Biology
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| 653 |
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|a Biomedical engineering
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| 653 |
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|a Population genetics
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| 653 |
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|a Probability Theory
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| 653 |
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|a Biomedical Engineering and Bioengineering
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| 653 |
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|a System theory
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| 653 |
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|a Population Genetics
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| 653 |
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|a Mathematical physics
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| 653 |
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|a Theoretical, Mathematical and Computational Physics
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| 653 |
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|a Probabilities
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| 700 |
1 |
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|a Tyran-Kamińska, Marta
|e [author]
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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-
|
| 490 |
0 |
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|a SpringerBriefs in Mathematical Methods
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-61295-9
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-61295-9?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 576.58
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| 520 |
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|a This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological proc essesinto a unified mathematical theory, and to arrive at revealing biological conclusions. The target audience primarily comprises of researchers in these two fields, but the book will also benefit graduate students
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