Welcome to Central Library, SUST
Amazon cover image
Image from Amazon.com
Image from Google Jackets

Mathematics for the Life Sciences [electronic resource] : Calculus, Modeling, Probability, and Dynamical Systems / by Glenn Ledder.

By: Contributor(s): Material type: TextTextSeries: Springer Undergraduate Texts in Mathematics and TechnologyPublisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: XX, 431 p. 109 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781461472766
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 570.285 23
LOC classification:
  • QH323.5
  • QH324.2-324.25
Online resources:
Contents:
A Brief Summary of Calculus -- Mathematical Modeling -- Probability Distributions -- Working with Probability -- Dynamics of Single Populations -- Discrete Dynamical Systems -- Continuous Dynamical Systems. - Index.
In: Springer eBooksSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

A Brief Summary of Calculus -- Mathematical Modeling -- Probability Distributions -- Working with Probability -- Dynamics of Single Populations -- Discrete Dynamical Systems -- Continuous Dynamical Systems. - Index.

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.

There are no comments on this title.

to post a comment.