  Networks describe a variety of interacting complex systems in social science,
biology and information technology. Usually the nodes of real networks are
identified not only by their connections but also by some other
characteristics. Examples of characteristics of nodes can be age, gender or
nationality of a person in a social network, the abundance of proteins in the
cell taking part in a protein-interaction networks or the geographical position
of airports that are connected by directed flights. Integrating the information
on the connections of each node with the information about its characteristics
is crucial to discriminating between the essential and negligible
characteristics of nodes for the structure of the network. In this paper we
propose a general indicator, based on entropy measures, to quantify the
dependence of a network's structure on a given set of features.
  We apply this method to social networks of friendships in US schools, to the
protein-interaction network of Saccharomyces cerevisiae and to the US airport
network, showing that the proposed measure provides information which
complements other known measures.
