Branching Processes in Biology (Interdisciplinary Applied Mathematics, Band 19) - Softcover

Kimmel, Marek; Axelrod, David E.

 
9781441929587: Branching Processes in Biology (Interdisciplinary Applied Mathematics, Band 19)

Inhaltsangabe

This book introduces biological examples of Branching Processes from molecular and cellular biology as well as from the fields of human evolution and medicine and discusses them in the context of the relevant mathematics, providing a useful introduction to how the modelling can be done and for what types of problems branching processes can be useful. As an aid to understanding specific examples, two introductory chapters provide background material in mathematics and biology. Scientists who work in quantitative modelling of biological systems, particularly probabilists, mathematical biologists, biostatisticians,

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Über die Autorin bzw. den Autor

Marek Kimmel is a Professor of Statistics at Rice University. Professor Kimmel's research focuses on probabilistic modeling and statistical analysis in biosciences. He is particularly interested in applications of his work in cell and molecular biology and in cancer research. From the mathematical point of view, his interests lie in Markov and branching processes and in estimation theory. David Axelrod is a Professor at Rutgers University, where he works in a laboratory focusing on the heterogeneity and progression of human breast cancers using methods of molecular biology, cell biology, computer simulation, and mathematical modeling.

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This book provides a theoretical background of branching process and discusses their biological applications. Branching processes are a well-developed and powerful set of tools in the field of applied probability. The range of applications considered includes molecular biology, cellular biology, human evolution, and medicine. The branching processes discussed include Galton-Watson, Markov, Bellman-Harris, Multitype, and General Processes. As an aid to understanding specific examples, two introductory chapters and two glossaries are included that provide background material in mathematics and in biology.

The book will be of interest to scientists who work in quantitative modeling of biological systems, particularly probabilists, mathematical biologists, biostatisticians, cell biologists, molecular biologists, and bioinformaticians.

The authors are a mathematician and cell biologist who have collaborated for more than a decade in the field of branching processes in biology.

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