European University Institute Library

Piecewise Deterministic Processes in Biological Models, by Ryszard Rudnicki, Marta Tyran-Kamińska

Label
Piecewise Deterministic Processes in Biological Models, by Ryszard Rudnicki, Marta Tyran-Kamińska
Language
eng
resource.imageBitDepth
0
Literary Form
non fiction
Main title
Piecewise Deterministic Processes in Biological Models
Medium
electronic resource
Nature of contents
dictionaries
Oclc number
1021277125
Responsibility statement
by Ryszard Rudnicki, Marta Tyran-Kamińska
Series statement
Springer eBooksSpringerBriefs in Applied Sciences and Technology,, 2191-530X
Summary
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 processes into 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.--, Provided by publisher
Table Of Contents
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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