000			03796nam a22004335i 4500
001			u372858
003			SIRSI
005			20160812084118.0
007			cr nn 008mamaa
008			100702s2010 xxk| s |||| 0|eng d
020			_a9781849962148 _9978-1-84996-214-8
040			_cMX-MeUAM
050		4	_aR856-857
082	0	4	_a610.28 _223
100	1		_aChen, Luonan. _eauthor.
245	1	0	_aModeling Biomolecular Networks in Cells _h[recurso electrónico] : _bStructures and Dynamics / _cby Luonan Chen, Ruiqi Wang, Chunguang Li, Kazuyuki Aihara.
264		1	_aLondon : _bSpringer London, _c2010.
300			_aXII, 343 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aDynamical Representations of Molecular Networks -- Deterministic Structures of Biomolecular Networks -- Qualitative Analysis of Deterministic Dynamical Networks -- Stability Analysis of Genetic Networks in Lur’e Form -- Design of Synthetic Switching Networks -- Design of Synthetic Oscillating Networks -- Multicellular Networks and Synchronization.
520			_aTaking ideas from nature has been a theme of humanity’s technological progress but it is only our newfound expertise in molecular manipulation and complex nonlinear dynamics that allows us the prospect of conscripting the building blocks of life as a means of furthering our abilities in circuits, systems and computers by the control of cellular networks. Modeling Biomolecular Networks in Cells shows how the interaction between the molecular components of basic living organisms can be modelled mathematically and the models used to create artificial biological entities within cells. Such forward engineering is a difficult task because of the ill-posed nature of the problems and because of the fundamental complexity of the interactions within even the most primitive biological cell. The nonlinear dynamical methods espoused in this book simplify the biology so that it can be successfully understood and the synthesis of simple biological oscillators and rhythm-generators made feasible. Such simple but, from an engineering point of view, unconventional units can then be co-ordinated using intercellular signal biomolecules. The formation of such man-made multicellular networks with a view to the production of biosensors, logic gates, new forms of integrated circuitry based on "gene-chips" and even biological computers is an important step in the design of faster and more flexible "electronics" for the future. The book also provides theoretical frameworks and tools with which to analyze the nonlinear dynamical phenomena, such as collective behaviour, which arise from the connection of building blocks in a biomolecular network. Researchers and graduate students from a variety of disciplines: engineering, applied mathematics, computer science and quantitative biology will find this book instructive and valuable. The text assumes a basic understanding of differential equations and the necessary molecular biology is dealt with chapter by chapter so only high-school biology is required.
650		0	_aEngineering.
650		0	_aBiomedical engineering.
650	1	4	_aEngineering.
650	2	4	_aBiomedical Engineering.
700	1		_aWang, Ruiqi. _eauthor.
700	1		_aLi, Chunguang. _eauthor.
700	1		_aAihara, Kazuyuki. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781849962131
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-84996-214-8
596			_a19
942			_cLIBRO_ELEC
999			_c200738 _d200738