The main aim of this paper is to introduce a mathematical frame- work to study stochastically evolving networks. More precisely, we provide a common language and suitable tools to study systematically the probability distribution of topological characteristics, which, in turn, play a key role in ap- plications, especially for biological networks. The latter is possible via suitable definition of a random network process and new results for graph isomorphism, which, under suitable generic assumptions, can be stated in terms of the graph walk matrix and computed in polynomial time.
All Science Journal Classification (ASJC) codes
- Applied Mathematics
- Statistics and Probability
- Computer Science Applications
- Biological networks
- Dynamic networks
- Isomorphic graphs