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007			cr nn 008mamaa
008			150903s2010 xxk| o |||| 0|eng d
020			_a9781849963961 _99781849963961
024	7		_a10.1007/9781849963961 _2doi
035			_avtls000344713
039		9	_a201509030424 _bVLOAD _c201405050311 _dVLOAD _y201402061304 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTK5105.5-5105.9
100	1		_aEstrada, Ernesto. _eeditor. _9321806
245	1	0	_aNetwork Science : _bComplexity in Nature and Technology / _cedited by Ernesto Estrada, Maria Fox, Desmond J. Higham, Gian-Luca Oppo.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2010.
300			_axI, 245 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aComplex Networks: An Invitation -- Resistance Distance, Information Centrality, Node Vulnerability and Vibrations in Complex Networks -- From Topology to Phenotype in Protein–Protein Interaction Networks -- Networks and Models with Heterogeneous Population Structure in Epidemiology -- NESSIE: Network Example Source Supporting Innovative Experimentation -- Networks in Urban Design. Six Years of Research in Multiple Centrality Assessment -- The Structure of Financial Networks -- A Hierarchy of Networks Spanning from Individual Organisms to Ecological Landscapes -- Revealing Structure of Complex Biological Systems Using Bayesian Networks -- Dynamics and Statistics of Extreme Events -- Dynamics of Networks of Leaky-Integrate-and-Fire Neurons.
520			_aConnections are important: in studying nature, technology, commerce and the social sciences, it often makes sense to focus on the pattern of interactions between individual components. Furthermore, improvements in computing power have made it possible to gather, store and analyze large data sets across many disciplines, and it is apparent that universal features may exist across seemingly disparate application areas. Network Science is the emerging field concerned with the study of large, realistic networks. This interdisciplinary endeavor, focusing on the patterns of interactions that arise between individual components of natural and engineered systems, has been applied to data sets from activities as diverse as high-throughput biological experiments, online trading information, smart-meter utility supplies, and pervasive telecommunications and surveillance technologies. This unique text/reference provides a fascinating insight into the state of the art in network science, highlighting the commonality across very different areas of application and the ways in which each area can be advanced by injecting ideas and techniques from another. The book includes contributions from an international selection of experts, providing viewpoints from a broad range of disciplines. It emphasizes networks that arise in nature - such as food webs, protein interactions, gene expression, and neural connections - and in technology - such as finance, airline transport, urban development and global trade. Topics and Features: Begins with a clear overview chapter to introduce this interdisciplinary field Discusses the classic network science of fixed connectivity structures, including empirical studies, mathematical models and computational algorithms Examines time-dependent processes that take place over networks, covering topics such as synchronization, and message passing algorithms Investigates time-evolving networks, such as the World Wide Web and shifts in topological properties (connectivity, spectrum, percolation) Explores applications of complex networks in the physical and engineering sciences, looking ahead to new developments in the field Researchers and professionals from disciplines as varied as computer science, mathematics, engineering, physics, chemistry, biology, ecology, neuroscience, epidemiology, and the social sciences will all benefit from this topical and broad overview of current activities and grand challenges in the unfolding field of network science. Dr. Ernesto Estrada is a professor in the Department of Mathematics and Statistics, and the Department of Physics, at the University of Strathclyde, Glasgow, Scotland. Dr. Maria Fox is a professor and head of the Computer and Information Sciences Department at the University of Strathclyde. Dr. Des Higham is a professor in the Department of Mathematics and Statistics at the University of Strathclyde. Dr. Gian-Luca Oppo is a professor and chair of Computational and Nonlinear Physics in the Department of Physics at the University of Strathclyde.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aFox, Maria. _eeditor. _9321807
700	1		_aHigham, Desmond J. _eeditor. _9306139
700	1		_aOppo, Gian-Luca. _eeditor. _9321808
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781849963954
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-84996-396-1 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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