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008 130828s2013 xxu| s |||| 0|eng d
020 _a9781461472766
_9978-1-4614-7276-6
024 7 _a10.1007/978-1-4614-7276-6
_2doi
050 4 _aQH323.5
050 4 _aQH324.2-324.25
072 7 _aPDE
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a570.285
_223
100 1 _aLedder, Glenn.
_eauthor.
245 1 0 _aMathematics for the Life Sciences
_h[electronic resource] :
_bCalculus, Modeling, Probability, and Dynamical Systems /
_cby Glenn Ledder.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXX, 431 p. 109 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Undergraduate Texts in Mathematics and Technology,
_x1867-5506
505 0 _aA Brief Summary of Calculus -- Mathematical Modeling -- Probability Distributions -- Working with Probability -- Dynamics of Single Populations -- Discrete Dynamical Systems -- Continuous Dynamical Systems. - Index.
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 _aMathematics.
650 0 _aLife sciences.
650 0 _aDynamics.
650 0 _aErgodic theory.
650 0 _aBiomathematics.
650 1 4 _aMathematics.
650 2 4 _aMathematical and Computational Biology.
650 2 4 _aLife Sciences, general.
650 2 4 _aDynamical Systems and Ergodic Theory.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461472759
830 0 _aSpringer Undergraduate Texts in Mathematics and Technology,
_x1867-5506
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-7276-6
912 _aZDB-2-SMA
942 _2Dewey Decimal Classification
_ceBooks
999 _c44849
_d44849