000			03352nam a22004095i 4500
001			978-0-387-09794-7
003			DE-He213
005			20250710083925.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387097947 _a99780387097947
024	7		_a10.1007/978-0-387-09794-7 _2doi
082	0	4	_a610 _223
100	1		_aMaroto, Miguel. _eeditor.
245	1	0	_aCellular Oscillatory Mechanisms _h[recurso electrónico] / _cedited by Miguel Maroto, Nicholas A. M. Monk.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aAdvances in Experimental Medicine and Biology, _x0065-2598 ; _v641
505	0		_aCalcium Oscillations -- Oscillations by the p53-Mdm2 Feedback Loop -- cAMP Oscillations during Aggregation of Dictyostelium -- Min Oscillation in Bacteria -- Development on Time -- Oscillatory Expression of Hes Family Transcription Factors: Insights from Mathematical Modelling -- Reverse Engineering Models of Cell Cycle Regulation -- Mitochondrial Oscillations in Physiology and Pathophysiology -- Respiratory Oscillations in Yeasts -- Stochastic Phase Oscillator Models for Circadian Clocks.
520			_aThe chapters in this book provide an introduction to a range of both well known and less familiar cellular oscillations and serve to illustrate the striking richness of cellular dynamics. The contributions focus particularly on elucidating the basic mechanisms that underlie these oscillations. The essentially quantitative nature of oscillations has long made them an attractive area of study for theoretical biologists, and the application of complementary modelling and experimental approaches can yield insights into oscillatory dynamics that go beyond those that can be obtained by either in isolation. The benefits of this synergy are reflected in the contributions appearing in this book. The current resurgence in interest in interdisciplinary approaches to cell and molecular biology stems in part from the increasing availability of system-wide data on the state of the components of cellular regulatory networks. Alimiting factor in these approaches is often the lack of suitable ways of characterising a network state in terms of summary quantitative features. Without such features, it is typically difficult to gain new qualitative insight into the operating logic of all but the simplest networks. In this regard, oscillatory phenomena provide ideal exemplars for systems approaches, since oscillations have clear summary features that prove invaluable in combining mathematical models with experimental data.
650		0	_aMEDICINE.
650	1	4	_aBIOMEDICINE.
650	2	4	_aBIOMEDICINE GENERAL.
700	1		_aMonk, Nicholas A. M. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387097930
830		0	_aAdvances in Experimental Medicine and Biology, _x0065-2598 ; _v641
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-09794-7 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SBL
942			_2ddc _cER
999			_c56072 _d56072