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Alan Garfinkel, Yina Guo, Jane Shevtsov (Beteiligte)

Modeling Life


The Mathematics of Biological Systems
1st ed. 2017. 2017. xv, 445 S. 54 SW-Abb., 299 Farbabb., 346 Farbtabellen. 254 mm
Verlag/Jahr: SPRINGER, BERLIN; SPRINGER INTERNATIONAL PUBLISHING 2017
ISBN: 3-319-59730-2 (3319597302)
Neue ISBN: 978-3-319-59730-0 (9783319597300)

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This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions.
Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler´s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking.

Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?
1. Modeling, Change, and Simulation.- 2. Derivatives and Integrals.- 3. Equilibrium Behavior.- 4. Non-Equilibrium Dynamics: Oscillation.- 5. Chaos.- 6. Linear Algebra.- 7. Multivariable Systems.- Bibliography.- Index.
"The book can serve as an introduction to the field of modeling not only for university students but for any person interested in the field with little or no knowledge of calculus. ... This book is a very interesting deviation from this prevailing paradigm. It takes the essence of calculus and presents it in a way which is accessible and usable in the practice of life sciences professionals." (Svetoslav Markov, zbMATH 1397.92001, 2018)