By Sitabhra Sinha (auth.), Niloy Ganguly, Andreas Deutsch, Animesh Mukherjee (eds.)
This self-contained booklet systematically explores the statistical dynamics on and of complex networks having relevance throughout various clinical disciplines. virtually any large-scale process, both evidently happening or man-made, may be seen as a fancy community of interacting entities dynamically evolving through the years. consequently, the theories concerning advanced networks are more and more getting used by means of researchers for his or her usefulness in harnessing the main tough difficulties of a selected discipline.
The booklet is a suite of surveys and state-of-the-art study contributions exploring the interdisciplinary dating of dynamics on and of advanced networks. in the direction of this objective, the paintings is thematically prepared into 3 major sections: half I reports the appliance of advanced networks to organic difficulties; half II specializes in social networks; and half III is an outline of networks wide-spread within the info sciences.
Specific subject matters and lines include:
* complete and concise presentation of present examine from specialists in quite a few disciplines compiled in a single volume
* suitable studies of vital paintings within the box (8 chapters) giving the reader an up to date photo of the state-of-the-art
* autonomous examine studies (8 chapters) offering transparent conceptions of the way complicated networks might be super worthwhile to accommodate tricky difficulties in quite a few disciplines
* insurance of complicated networks present in nature—genetic pathways, ecological networks, linguistic structures, and social systems—as good as man-made structures reminiscent of the realm vast net 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 different examine components, and should be worthwhile to newbies within the box, skilled researchers, practitioners, and graduate scholars drawn to platforms displaying an underlying advanced community constitution in disciplines corresponding to computing device technology, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.
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Additional info for Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences
Although all large-scale studies are subject to noise, the rationale for data integration is that observations of true interactions will reinforce or complement one another when combined across diﬀerent studies and/or experimental techniques. For example, the independent observation of a protein-protein interaction by both Y2H and TAP-MS methods, or by two independent TAP-MS studies, renders this interaction more likely to be true . Network-Based Models in Molecular Biology 41 Such evidences for interaction can be further supported by including other types of data that are not necessarily measurements of direct physical contact.
14. A. Hoﬀmann, A. L. Scott, and D. Baltimore. The IκB-NFκB signaling module: temporal control and selective gene activation. Science, 298:1241– 1245, 2002. 15. C. Ihekwaba, D. Broomhead, R. Grimley, N. B. Kell. Sensitivity analysis of parameters controlling oscillatory signalling in the NF-κB pathway: the roles of IKK and IκBα. IEE Syst. , 1:93–103, 2004. 16. G. Lahav, N. Rosenfeld, A. Sigal, N. J. Levine, M. Elowitz, and U. Alon. Dynamics of the p53-Mdm2 feedback loop in individual cells. Nat.
Gene-gene networks. Gene-gene networks are not molecular networks, but in fact logical networks: they describe functional relationships between genes. For example, two genes may be linked if their products participate in the same process or pathway. Such functional networks have been created by integrating diverse evidence for common functions of genes [45, 59]. For example, the fact that two genes appear together in many species (common phylogenetic proﬁle) indicates that the genes participate in a common process.