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• W2114585280 abstract "*Correspondence: cgg@unam.mx 1Universidad Nacional Autonoma de Mexico, A.P. 20-726, 01000 Mexico city, D.F, Mexico Full list of author information is available at the end of the article Complex systems and networks Complex Adaptive Systems (CAS) or complex systems are characterized by the interactions between their numerous elements. The word ‘complex’ comes from the Latin plexus which means entwined. In other words, it is difficult to correlate global properties of complex systems with the properties of the individual constituent components. This is primarily because the interactions between these individual elements partly determine the future states of the system (Gershenson 2013). If these interactions are not included in the developed models, the models would not be an accurate reflection of the modelled phenomenon. While numerous techniques and frameworks for modeling complex systems have previously been devised (Niazi 2011), clearly one of the most explicit and intuitive methodology is the modeling of interactions using networks (Niazi and Hussain 2012). Networks consist of nodes or vertices, which can be used to represent elements, and links or edges, which usually represent interactions or relations between the elements. In this context, networks represent the structure of complex systems; how elements interact. However, networks can also be used to represent the dynamics or function of complex systems, e.g. considering nodes as states and links as transitions. Thus, the same analysis can be applied to the structure and the function of networks. Understanding the relationship between structure and function is one of the major open questions across sciences, which can also be posed using networks: how do changes in the structural network affect the state network? (Boccaletti et al. 2006; Gershenson 2012). For example, what will be the effect of knocking out a gene in the behavior of a cell? Several systems change their structure over time, and their properties can be modelled with temporal networks (Holme and Saramaki 2012). Likewise, there are several instances when the structural changes are triggered by the state of the network, as has been studied in adaptive networks (Gross and Sayama 2009). With not much more than a decade of network research, there are already numerous applications of networks in diverse areas, such as epidemiology (Colizza et al. 2007; Christakis and Fowler 2007; Pastor-Satorras and Vespignani 2001), human mobility (Gonzalez et al. 2008), social networks (Huberman et al. 2009; Niazi and Hussain 2011), artificial life (Gershenson and Prokopenko 2011), life sciences (Bullmore and Sporns 2009; Gershenson 2004; Guimera and Nunes Amaral 2005; Montoya et al. 2006), theory of" @default.
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• W2114585280 date "2013-11-08" @default.
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• W2114585280 title "Multidisciplinary applications of complex networks modeling, simulation, visualization, and analysis" @default.
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• W2114585280 doi "https://doi.org/10.1186/2194-3206-1-17" @default.
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