Exploring the organisation of complex systems through the dynamical interactions among their relevant subsets

Complex systems often show forms of organisation where a clear-cut hierarchy of levels with a well-defined direction of information flow cannot be found. In this paper we propose an information-theoretic method aimed at identifying the dynamically relevant parts of a system along with their relationships, interpreting in such a way the system’s dynamical organisation. The analysis is quite general and can be applied to many dynamical systems. We show here its application to two relevant biological examples, the case of mammalian cell cycle network and of Mitogen Activated Protein Kinase (MAPK) cascade. The result of our analysis shows that the elements of the mammalian cell cycle network act as a single compact group, whereas the MAPK system can be decomposed into two dynamically distinct parts, with asymmetric information flows.