This article is 'Highly accessed' (total accesses to this article since publication: 1197) relative to age in BioMed Central: Increasing risk behaviour can outweigh the benefits of antiretroviral drug treatment on the HIV incidence among men-having-sex-with-men in Amsterdam Shan Mei, Rick Quax, David VAN de Vijver, Yifan Zhu and P.m.a. Sloot BMC Infectious Diseases, 11:118 (11 May 2011)
As of August 27, the most downloaded/accessed paper in BMC Systems Biology is: D. van Dijk et al.: Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks, BMC Systems Biology, vol. 4, nr 1 pp. 96+17. 2010.
This paper received the ICCS best paper award 2010:
N. Zarrabi et al.: Modeling HIV-1 intracellular replication, Procedia Computer Science vol. 1, nr 1 pp. 555-564. Elsevier B.V., Amsterdam, May 2010.
This is the home page for the DynaNets EU FP7 FET Open project, started June 1, 2009.
Recent advances in experimental techniques such as detectors, sensors, and scanners have opened up new windows into physical and biological processes on many levels of detail. The complete cascade from the individual components to the fully integrated multi-science systems crosses many orders of magnitude in temporal and spatial scales. The challenge is to study not only the fundamental processes on all these separate scales, but also their mutual coupling through the scales in the overall system, and the resulting emergent properties. These complex systems display endless signatures of order, disorder, self-organization and self-annihilation. Understanding, quantifying and handling this information complexity is one of the biggest scientific challenges of our time. Amazingly nature seems to be able to process information on many spatial scales simultaneously. DynaNets will study and develop a new paradigm of computing through Dynamically Changing Complex Networks reproducing the way nature processes information. It will develop theory and methods of dynamical networks providing us with new insights into the underlying processes of nature, economy, and society. As a pilot study we will investigate the dynamics of the HIV and influenza epidemics from the molecule all the way up to the population.
DynaNets will study and develop a new paradigm of computing through Dynamically Changing Complex Networks, reproducing the way nature processes information.
Objective O1: Achieving control by developing a theory of spreading in networks, e.g. of infections and the transmission of drug resistance
Objective O2: Understanding real-world dynamically changing networks, for example contact networks such as in HIV
Objective O3: Valorisation of theory in multiple application domains such as ecology and evolution