By Sitabhra Sinha (auth.), Niloy Ganguly, Andreas Deutsch, Animesh Mukherjee (eds.)
This self-contained e-book systematically explores the statistical dynamics on and of complex networks having relevance throughout a lot of clinical disciplines. nearly any large-scale process, both clearly taking place or man-made, might be seen as a posh community of interacting entities dynamically evolving through the years. as a result, the theories with regards to advanced networks are more and more getting used by means of researchers for his or her usefulness in harnessing the main tricky difficulties of a selected discipline.
The publication is a set of surveys and state of the art examine contributions exploring the interdisciplinary courting of dynamics on and of complicated networks. in the direction of this objective, the paintings is thematically geared up into 3 major sections: half I reviews the appliance of advanced networks to organic difficulties; half II specializes in social networks; and half III is an summary of networks common within the info sciences.
Specific themes and contours include:
* entire and concise presentation of present examine from specialists in numerous disciplines compiled in a single volume
* proper studies of vital paintings within the box (8 chapters) giving the reader an updated photograph of the state-of-the-art
* self reliant examine studies (8 chapters) supplying transparent conceptions of the way complicated networks might be tremendous valuable to house tricky difficulties in various disciplines
* insurance of advanced networks present in nature—genetic pathways, ecological networks, linguistic structures, and social systems—as good as man-made structures equivalent to the area huge internet and peer-to-peer networks
* A thesaurus of crucial phrases on the topic of advanced networks for speedy and straightforward reference
The contributed chapters during this quantity are meant to advertise cross-fertilization in numerous examine parts, and may be worthwhile to newbies within the box, skilled researchers, practitioners, and graduate scholars attracted to platforms displaying an underlying advanced community constitution in disciplines resembling machine technology, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.
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Additional resources for Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences
Phys. Rev. E, 76, 015101(R) (2007) 26. : Spatiotemporal dynamics of networks of excitable nodes. Chaos, 16, 015110 (2006) 27. : Exploring complex networks. Nature, 410, 268–276 (2001) 28. : Collective dynamics of ‘small-world’ networks. Nature, 393, 440–442 (1998) 29. : Complexity in biological signaling systems. Science, 284, 92–96 (1999) 30. : Examining the eﬀects of species richness on community stability: An assembly model approach. Oikos, 99, 363–367 (2002) 31. : Understanding ecosystem robustness.
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The qualitative behaviour of a system can be seen as an emergent property of this structure. Boolean models are especially useful in the case of large networks [1, 9], for which kinetic parameters are often unknown, but qualitative properties such as generation of speciﬁc gene expression patterns, stability or multistability, and oscillatory modes can be studied. Several methods have been developed for analysis of discrete and qualitative models [2, 5, 7, 13, 26]. Using an approach which combines discrete rules with continuous degradation rates, our model reproduces many of the known properties of the system, notably the oscillatory dynamics that can be induced by the NFκB-IκB negative feedback loop [14, 15, 19].
Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences by Sitabhra Sinha (auth.), Niloy Ganguly, Andreas Deutsch, Animesh Mukherjee (eds.)