Resumen de Structural and dynamical interdependencies in complex networks at meso- and macroscale: nestedness, modularity, and in-block nestedness
Many real systems like the financial market or the brain, can, in a broad sense, be said to be complex, i.e., they are made of a large number of interacting components, and display collective behavior that can not be inferred from the behaviors of the individual parts. A particular approach to study them is to consider them as networks, with its components represented as nodes and the interactions between them as links. Under this view, we find a large body of research focused on putting to light the interplay between structure and dynamics: exploring how the dynamical behavior of the network is constrained by the nature of the interactions between its elements, as well as by the topology of such interactions. These analyses are usually performed at three scales: the microscale based on single nodes, the macroscale that explores the whole network, and the mesoscale that study groups of nodes. Nonetheless, most studies so far have focused on either of them, despite the increasing evidence suggesting that networks often exhibit structures at several scales of organization. In this thesis, we apply structural network analysis to a variety of synthetic and empirical systems at meso- and macroscale. We focus on an examination of nestedness, modularity, and in-block nested patterns and the relationship and effects that they impose on each other. Finally, we introduce an ecology-inspired theoretical model that helps us to better understand some of the mechanisms that enable the emergence of such arrangements.
