000 03050cam a22002177i 4500
999 _c1666
_d1666
005 20180201143032.0
008 130521s2013 nyua b 001 0 eng
020 _a9781461472759 (hbk : acidfree paper)
020 _a146147275X (hbk : acidfree paper)
040 _aB-IKIAM
041 _aENG
082 0 4 _a570.15118
_bL472
100 1 _aLedder, Glenn,
245 1 0 _aMathematics for the life sciences :
_bcalculus, modeling, probability, and dynamical systems /
_cGlenn Ledder.
264 1 _aNew York :
_bSpringer,
_c[2013]
300 _axx, 431 pages :
_billustrations ;
_c27 cm.
505 0 _aA brief summary of calculus -- Mathematical modeling -- Probability distributions -- Working with probability -- Dynamics of single populations -- Discrete dynamical systems -- Continuous dynamical systems -- Appendix A. Additional topics in discrete dynamical systems -- Appendix B. The definite integral via Riemann sums -- Appendix C. A Runge-Kutta method for numerical solution of differential equations -- Hints and answeres to selected problems.
520 _aMathematics 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.
650 0 _aBiology
942 _2ddc
_aB-IKIAM
_b2018
_cBK
_zbv