| 000 | 02980nam a22005175i 4500 | ||
|---|---|---|---|
| 001 | 978-4-431-53862-2 | ||
| 003 | DE-He213 | ||
| 005 | 20140220084553.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100319s2010 ja | s |||| 0|eng d | ||
| 020 |
_a9784431538622 _9978-4-431-53862-2 |
||
| 024 | 7 |
_a10.1007/978-4-431-53862-2 _2doi |
|
| 050 | 4 | _aR856-857 | |
| 072 | 7 |
_aMQW _2bicssc |
|
| 072 | 7 |
_aTEC009000 _2bisacsh |
|
| 082 | 0 | 4 |
_a610.28 _223 |
| 100 | 1 |
_aDoi, Shinji. _eauthor. |
|
| 245 | 1 | 0 |
_aComputational Electrophysiology _h[electronic resource] : _bDynamical Systems and Bifurcations / _cby Shinji Doi, Junko Inoue, Zhenxing Pan, Kunichika Tsumoto. |
| 264 | 1 |
_aTokyo : _bSpringer Japan : _bImprint: Springer, _c2010. |
|
| 300 |
_a140p. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aA First Course in “In Silico Medicine” ; _v2 |
|
| 505 | 0 | _aA 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. | |
| 520 | _aBiological 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. | ||
| 650 | 0 | _aEngineering. | |
| 650 | 0 | _aMedicine. | |
| 650 | 0 | _aBiochemistry. | |
| 650 | 0 | _aBiomedical engineering. | |
| 650 | 1 | 4 | _aEngineering. |
| 650 | 2 | 4 | _aBiomedical Engineering. |
| 650 | 2 | 4 | _aMolecular Medicine. |
| 650 | 2 | 4 | _aMedicinal Chemistry. |
| 700 | 1 |
_aInoue, Junko. _eauthor. |
|
| 700 | 1 |
_aPan, Zhenxing. _eauthor. |
|
| 700 | 1 |
_aTsumoto, Kunichika. _eauthor. |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9784431538615 |
| 830 | 0 |
_aA First Course in “In Silico Medicine” ; _v2 |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-4-431-53862-2 |
| 912 | _aZDB-2-ENG | ||
| 999 |
_c113075 _d113075 |
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