Biological Systems: Nonlinear Dynamics Approach

Herausgegeben:Carballido-Landeira, Jorge; Escribano, Bruno

• Gebundenes Buch

Produktbeschreibung

This book collects recent advances in the field of nonlinear dynamics in biological systems. Focusing on medical applications as well as more fundamental questions in biochemistry, it presents recent findings in areas such as control in chemically driven reaction-diffusion systems, electrical wave propagation through heart tissue, neural network growth, chiral symmetry breaking in polymers and mechanochemical pattern formation in the cytoplasm, particularly in the context of cardiac cells.

It is a compilation of works, including contributions from international scientists who attended the "2nd BCAM Workshop on Nonlinear Dynamics in Biological Systems," held at the Basque Center for Applied Mathematics, Bilbao in September 2016. Embracing diverse disciplines and using multidisciplinary approaches - including theoretical concepts, simulations and experiments - these contributions highlight the nonlinear nature of biological systems in order to be able toreproducetheir complex behavior. Edited by the conference organizers and featuring results that represent recent findings and not necessarily those presented at the conference, the book appeals to applied mathematicians, biophysicists and computational biologists.

Produktdetails

• SEMA SIMAI Springer Series 20
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-16584-0
• 1st ed. 2019
• Seitenzahl: 116
• Erscheinungstermin: 9. Mai 2019
• Englisch
• Abmessung: 241mm x 160mm x 13mm
• Gewicht: 322g
• ISBN-13: 9783030165840
• ISBN-10: 3030165841
• Artikelnr.: 55330396

Autorenporträt

Jorge Carballido-Landeira received his PhD degree in Physics from the University of Santiago de Compostela (Spain) in 2011, where he worked on nonlinear physical dynamics emerging in active confined chemical systems. He is currently an Assistant Professor at the Department of Applied Physics at the University of Oviedo, Spain. His research focuses on a multidisciplinary field that includes nonlinear dynamics, self-organization processes, colloidal and polymer science, environmental constraints and fluid mechanics in order to gain an understanding of complex biological systems. Bruno Escribano has been a researcher at the Basque Center for Applied Mathematics since 2014. He holds a PhD in Physics and Mathematics from the University of Granada, Spain (2010). His highly multidisciplinary research focuses on such diverse topics as astrophysics, quasi-crystals, biomineralization and pattern formation in geophysics. His current research interests are related to the modeling and simulation of biological systems using nonlinear dynamical methods.

Inhaltsangabe

1 J. Carballido-Landeira and B. Escribano, Biological Systems: Nonlinear Dynamics approach.- 2 M. Stich and C. Beta, Time-delay feedback control of an oscillatory medium.- 3 A. Peñaranda et al., Electrophysiological effects of small conductance Ca2+-activated K+ channels in atrial myocytes.- 4 D. Hochberg et al., Spontaneous Mirror Symmetry Breaking from Recycling in Enantioselective Polymerization.- 5 D. de Santos-Sierra et al., Self-organized cultured neuronal networks: longitudinal analysis and modeling of the underlying network structure.- 6 S. Alonso, Onset of mechanochemical pattern formation in poroviscoelastic models of active cytoplasm.

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1 J. Carballido-Landeira and B. Escribano, Biological Systems: Nonlinear Dynamics approach.- 2 M. Stich and C. Beta, Time-delay feedback control of an oscillatory medium.- 3 A. Peñaranda et al., Electrophysiological effects of small conductance Ca2+-activated K+ channels in atrial myocytes.- 4 D. Hochberg et al., Spontaneous Mirror Symmetry Breaking from Recycling in Enantioselective Polymerization.- 5 D. de Santos-Sierra et al., Self-organized cultured neuronal networks: longitudinal analysis and modeling of the underlying network structure.- 6 S. Alonso, Onset of mechanochemical pattern formation in poroviscoelastic models of active cytoplasm.