Construcción de un algoritmo computacional para medir propiedades topológicas de redes de comunicación celular.

Abstract

The structure of cell signaling networks determines the dynamics of physiological processes in living organisms, processes that belong both to regular functions and diseases. In the area of complex networks some metrics are used to determine the topological structure of networks, such as the degree sequence, the local clustering coefficient, the closeness centrality, and the degree-degree correlations. Here, we built a computational algorithm to compute all these metrics both to characterize cell signaling networks and to find structural differences between the networks corresponding to regular and disease processes. Our results show some differences between both kinds of networks.