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Beskrivning
This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data.
Johannes Muller's research interest lies in the interface of mathematics and life sciences. In particular his research is concerned with the theory and biological applications of dynamical systems and branching processes.He studied in Karlsruhe and Tubingen, where he completed his habilitation in 2001. After stays in Utrecht and Cologne, he became head of a research group at the Institute for Biomathematics and Biometry at the Helmholtz Center, Munich. He has been appointed as a professor at the Technische Universitat Munchen (2004), where he is responsible for the masters program "Mathematics in Biosciences". Christina Kuttler is a professor at the Technical University Munich, her work focusing on "Mathematics in Life Sciences". She previously worked at the University of Tubingen and at the Helmholtz Center Munich, Institute for Biomathematics and Biometry, as part of the interdisciplinary project on molecular interactions in the rhizosphere. Her main expertise is in the field of biomathematics, particularly the mathematical modelling of biological processes using ordinary and partial differential equations. A main project deals with the modelling of bacterial communications, in which intracellular regulation mechanisms and diffusion processes are considered. Her primary goal is a better understanding of the underlying mechanisms and provide a quantitative description.
Recensioner i media
"The core of the book is based on a two-semester graduate course on the mathematical modeling of biological systems. In my opinion, the book is targeted at graduate students with a strong mathematics background. ... The book has a very nice diversity of topics in biology and applied dynamical systems. ... There is a nice bank of exercises, at the right level for first to second year graduate students." (Zachary P. Kilpatrick, SIAM Review, Vol. 59 (1), March, 2017)