Communicability and subgraph centrality in complex networks

Description
A gently introduction to the concept of communicability of networks from a combinatorial point of view. We analyse the use of communicability functions for detecting communities in networks and give some examples of their applications. The analysis of self-communicability or subgraph centrality is then motivated and some examples are provided for the study of protein interaction networks. The use of communicability functions for studying brain networks are also summarised. Finally, we will give a method based on communicabilities for the detection of communities in networks and will show some challenge examples of its application.
Organised by Vito Latora