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Applications of Dynamical Systems in Biology and Medicine Softcover reprint of the original 1st ed. 2015 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 233 pages, height x width: 235x155 mm, weight: 4262 g, 37 Illustrations, color; 42 Illustrations, black and white; XI, 233 p. 79 illus., 37 illus. in color., 1 Paperback / softback
  • Sērija : The IMA Volumes in Mathematics and its Applications 158
  • Izdošanas datums: 15-Oct-2016
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1493950088
  • ISBN-13: 9781493950089
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  • Mīkstie vāki
  • Cena: 91,53 €*
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  • Formāts: Paperback / softback, 233 pages, height x width: 235x155 mm, weight: 4262 g, 37 Illustrations, color; 42 Illustrations, black and white; XI, 233 p. 79 illus., 37 illus. in color., 1 Paperback / softback
  • Sērija : The IMA Volumes in Mathematics and its Applications 158
  • Izdošanas datums: 15-Oct-2016
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1493950088
  • ISBN-13: 9781493950089
Citas grāmatas par šo tēmu:
This volume highlights problems from a range of biological and medical applications that can be interpreted as questions about system behavior or control. Topics include drug resistance in cancer and malaria, biological fluid dynamics, auto-regulation in the kidney, anti-coagulation therapy, evolutionary diversification and photo-transduction. Mathematical techniques used to describe and investigate these biological and medical problems include ordinary, partial and stochastic differentiation equations, hybrid discrete-continuous approaches, as well as 2 and 3D numerical simulation. 

?Anti-Cancer Drug Resistance: A Pre-existing or Emerging Phenomenon?.- Modeling Fluid Flow Induced by Bacterial Carpets.- Modeling Auto regulation in the Kidney.- Modeling Anti-coagulation Therapy.- Mathematical Modeling of Evolutionary Diversification.- Intermittent Preventative Treatment (IPT) and the Spread of Drug Resistance to Malaria.- Stochastic Modeling of the Phototransduction Cascade for Melanopsin.- Clustering in Inhibitory Neural Networks with Nearest Neighbor Coupling.- Modeling the Dynamics of REM Sleep.