Computational Electrophysiology [recurso electrónico] : Dynamical Systems and Bifurcations / by Shinji Doi, Junko Inoue, Zhenxing Pan, Kunichika Tsumoto.
Tipo de material: TextoSeries A First Course in “In Silico Medicine” ; 2Editor: Tokyo : Springer Japan : Imprint: Springer, 2010Descripción: 140p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9784431538622Tema(s): Engineering | Medicine | Biochemistry | Biomedical engineering | Engineering | Biomedical Engineering | Molecular Medicine | Medicinal ChemistryFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 610.28 Clasificación LoC:R856-857Recursos en línea: Libro electrónicoTipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | R856 -857 (Browse shelf(Abre debajo)) | 1 | No para préstamo | 377200-2001 |
A Very Short Trip on Dynamical Systems -- The Hodgkin–Huxley Theory of Neuronal Excitation -- Computational and Mathematical Models of Neurons -- Whole System Analysis of Hodgkin–Huxley Systems -- Hodgkin–Huxley-Type Models of Cardiac Muscle Cells.
Biological systems inherently possess much ambiguity or uncertainty. Computational electrophysiology is the one area, from among the vast and rapidly growing discipline of computational and systems biology, in which computational or mathematical models have succeeded. This book provides a practical and quick guide to both computational electrophysiology and numerical bifurcation analysis. Bifurcation analysis is a very powerful tool for the analysis of such highly nonlinear biological systems. Bifurcation theory provides a way to analyze the effect of a parameter change on a system and to detect a critical parameter value when the qualitative nature of the system changes. Included in this work are many examples of numerical computations of bifurcation analysis of various models as well as mathematical models with different abstraction levels from neuroscience and electrophysiology. This volume will benefit graduate and undergraduate students as well as researchers in diverse fields of science.
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