LEADER 05603nam 22006855 450 001 9910299983203321 005 20250609110735.0 010 $a1-4614-9096-0 024 7 $a10.1007/978-1-4614-9096-8 035 $a(CKB)3710000000249653 035 $a(Springer)9781461490968 035 $a(MH)014199316-2 035 $a(SSID)ssj0001354199 035 $a(PQKBManifestationID)11810433 035 $a(PQKBTitleCode)TC0001354199 035 $a(PQKBWorkID)11322657 035 $a(PQKB)11728123 035 $a(DE-He213)978-1-4614-9096-8 035 $a(MiAaPQ)EBC5575538 035 $a(PPN)181346338 035 $a(MiAaPQ)EBC1997492 035 $a(EXLCZ)993710000000249653 100 $a20140918d2014 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMathematics as a Laboratory Tool $eDynamics, Delays and Noise /$fby John Milton, Toru Ohira 205 $a1st ed. 2014. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2014. 215 $a1 online resource (XXV, 500 p. 162 illus., 4 illus. in color.)$conline resource 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a1-4614-9095-2 320 $aIncludes bibliographical references and index. 327 $aScience and the mathematics of black boxes -- The mathematics of change -- Equilibria and steady states -- Stability -- Fixed?points: Creation and destruction -- Transient dynamics -- Frequency domain I: Bode plots and transfer functions -- Frequency domain II: Fourier analysis and power spectra -- Feedback and control systems -- Oscillations -- Beyond limit cycles -- Random perturbations -- Noisy dynamical systems -- Random walkers -- Thermodynamic perspectives. 330 $aThe importance of mathematics in the undergraduate biology curriculum is ever increasing, as is the importance of biology within the undergraduate applied mathematics curriculum. This ambitious forward thinking book  strives to make concrete  connections between the two fields at the undergraduate level, bringing in a wide variety of mathematical  methods  such as  signal processing, systems identification, and stochastic differential equations to an undergraduate audience interested in biological dynamics. The presentation stresses a practical hands-on approach: important concepts are introduced using linear first- or second-order differential equations that can be solved using ?pencil and paper?; next, these are extended to ?real world? applications through the use of computer algorithms written in Scientific Python or similar software. This book developed from a course taught by Professor John Milton at the University of Chicago and developed and continued over many years with Professor Toru Ohira at the Claremont Colleges. The tone of the book is pedagogical, engaging, accessible, with lots of examples and exercises. The authors attempt to tread a line between accessibility of the text and mathematical exposition. Online laboratories are provided as a teaching aid.  At the beginning of each chapter a number of questions are posed to the reader, and then answered at the conclusion of the chapter.     Milton and Ohira?s book is aimed at an undergraduate audience, makes close ties to the laboratory, and includes a range of biological applications, favoring  physiology. This makes it a unique contribution to the literature. This book will be of interest to quantitatively inclined undergraduate biologists, biophysicists and bioengineers and in addition through its focus on techniques actually used by biologists, the authors hope this  text will help shape curricula in biomathematics education going forward. Review: "Based on the authors' experience teaching biology students, this book introduces a wide range of mathematical techniques in a lively and engaging style.  Examples drawn from the authors' experimental and neurological studies provide a rich source of material for computer laboratories that solidify the concepts.  The book will be an invaluable resource for biology students and scientists interested in practical applications of mathematics to analyze mechanisms of complex biological rhythms."  (Leon Glass, McGill University, 2013). 606 $aBiomathematics 606 $aNeurology 606 $aCell physiology 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aNeurology$3https://scigraph.springernature.com/ontologies/product-market-codes/H36001 606 $aCell Physiology$3https://scigraph.springernature.com/ontologies/product-market-codes/L33010 615 0$aBiomathematics. 615 0$aNeurology. 615 0$aCell physiology. 615 14$aMathematical and Computational Biology. 615 24$aNeurology. 615 24$aCell Physiology. 676 $a570.1/5195 700 $aMilton$b John$4aut$4http://id.loc.gov/vocabulary/relators/aut$0308340 702 $aOhira$b Toru$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299983203321 996 $aMathematics as a Laboratory Tool$91903895 997 $aUNINA 999 $aThis Record contains information from the Harvard Library Bibliographic Dataset, which is provided by the Harvard Library under its Bibliographic Dataset Use Terms and includes data made available by, among others the Library of Congress