LEADER 04514nam 22007935 450 001 9910299787303321 005 20251116135429.0 010 $a3-319-20059-3 024 7 $a10.1007/978-3-319-20059-0 035 $a(CKB)3710000000454139 035 $a(SSID)ssj0001558527 035 $a(PQKBManifestationID)16182677 035 $a(PQKBTitleCode)TC0001558527 035 $a(PQKBWorkID)14819290 035 $a(PQKB)11532746 035 $a(DE-He213)978-3-319-20059-0 035 $a(MiAaPQ)EBC5587991 035 $a(Au-PeEL)EBL5587991 035 $a(OCoLC)913958079 035 $a(PPN)187690014 035 $a(EXLCZ)993710000000454139 100 $a20150706d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 12$aA Guide to Numerical Modelling in Systems Biology /$fby Peter Deuflhard, Susanna Röblitz 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (X, 168 p. 42 illus., 33 illus. in color.) 225 1 $aTexts in Computational Science and Engineering,$x1611-0994 ;$v12 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-319-20058-5 327 $aPreface -- Outline -- ODE Models for Systems Biological Networks -- Numerical Simulation of ODE Models -- Parameter Identification in ODE Models -- Appendix -- Software -- Index. 330 $aThis book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks, and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.  . 410 0$aTexts in Computational Science and Engineering,$x1611-0994 ;$v12 606 $aDifferential equations 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aBiomathematics 606 $aComputer simulation 606 $aPhysics 606 $aOrdinary Differential Equations$3https://scigraph.springernature.com/ontologies/product-market-codes/M12147 606 $aApplications of Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M13003 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000 606 $aNumerical and Computational Physics, Simulation$3https://scigraph.springernature.com/ontologies/product-market-codes/P19021 615 0$aDifferential equations. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 0$aBiomathematics. 615 0$aComputer simulation. 615 0$aPhysics. 615 14$aOrdinary Differential Equations. 615 24$aApplications of Mathematics. 615 24$aMathematical and Computational Biology. 615 24$aSimulation and Modeling. 615 24$aNumerical and Computational Physics, Simulation. 676 $a515.352 700 $aDeuflhard$b Peter$4aut$4http://id.loc.gov/vocabulary/relators/aut$067060 702 $aRo?blitz$b Susanna$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299787303321 996 $aA Guide to Numerical Modelling in Systems Biology$92504064 997 $aUNINA