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03935nam a22005055i 4500 |
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978-1-4614-7276-6 |
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DE-He213 |
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20151103121231.0 |
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cr nn 008mamaa |
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130828s2013 xxu| s |||| 0|eng d |
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|a 9781461472766
|9 978-1-4614-7276-6
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|a 10.1007/978-1-4614-7276-6
|2 doi
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|d GrThAP
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|a QH323.5
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|a QH324.2-324.25
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|a PDE
|2 bicssc
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|a MAT003000
|2 bisacsh
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|a 570.285
|2 23
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|a Ledder, Glenn.
|e author.
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|a Mathematics for the Life Sciences
|h [electronic resource] :
|b Calculus, Modeling, Probability, and Dynamical Systems /
|c by Glenn Ledder.
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| 264 |
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|a New York, NY :
|b Springer New York :
|b Imprint: Springer,
|c 2013.
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|a XX, 431 p. 109 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Springer Undergraduate Texts in Mathematics and Technology,
|x 1867-5506
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|a A Brief Summary of Calculus -- Mathematical Modeling -- Probability Distributions -- Working with Probability -- Dynamics of Single Populations -- Discrete Dynamical Systems -- Continuous Dynamical Systems. - Index.
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|a Mathematics for the Life Sciences provides present and future biologists with the mathematical concepts and tools needed to understand and use mathematical models and read advanced mathematical biology books. It presents mathematics in biological contexts, focusing on the central mathematical ideas, and providing detailed explanations. The author assumes no mathematics background beyond algebra and precalculus. Calculus is presented as a one-chapter primer that is suitable for readers who have not studied the subject before, as well as readers who have taken a calculus course and need a review. This primer is followed by a novel chapter on mathematical modeling that begins with discussions of biological data and the basic principles of modeling. The remainder of the chapter introduces the reader to topics in mechanistic modeling (deriving models from biological assumptions) and empirical modeling (using data to parameterize and select models). The modeling chapter contains a thorough treatment of key ideas and techniques that are often neglected in mathematics books. It also provides the reader with a sophisticated viewpoint and the essential background needed to make full use of the remainder of the book, which includes two chapters on probability and its applications to inferential statistics and three chapters on discrete and continuous dynamical systems. The biological content of the book is self-contained and includes many basic biology topics such as the genetic code, Mendelian genetics, population dynamics, predator-prey relationships, epidemiology, and immunology. The large number of problem sets include some drill problems along with a large number of case studies. The latter are divided into step-by-step problems and sorted into the appropriate section, allowing readers to gradually develop complete investigations from understanding the biological assumptions to a complete analysis.
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| 650 |
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|a Mathematics.
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| 650 |
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|a Life sciences.
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| 650 |
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|a Dynamics.
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| 650 |
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|a Ergodic theory.
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| 650 |
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|a Biomathematics.
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| 650 |
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4 |
|a Mathematics.
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| 650 |
2 |
4 |
|a Mathematical and Computational Biology.
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| 650 |
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4 |
|a Life Sciences, general.
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| 650 |
2 |
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|a Dynamical Systems and Ergodic Theory.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9781461472759
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| 830 |
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|a Springer Undergraduate Texts in Mathematics and Technology,
|x 1867-5506
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/978-1-4614-7276-6
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SMA
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| 950 |
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|a Mathematics and Statistics (Springer-11649)
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