The logical method proved useful for the modelling of regulatory networks and the analysis of their dynamical properties. It relies on two directed graphs: the regulatory graph, which represents the interactions between regulatory components, each associated with discrete levels of expression (or activity), and the state transition graph, which represents the discrete dynamics of such a model. This discrete modelling framework allows qualitative analyses of the behaviours driven by regulatory networks, based on analytical results or on simulation (i.e. construction of state transition graphs). Although this formalism abstracts and simplifies the biological reality, we still need to cope with challenging issues due to the complexity of ever increasing networks. We present here some results and tools that aim at facilitating the analysis of large networks. In particular, we will show how dynamical properties can be predicted from the presence of particular motifs in the regulatory graph, namely regulatory circuits and combination of such circuits. We will also discuss a method to reduce the model, yet keeping the main features of the dynamics. Finally, we will illustrate these approaches on a generic model of E2F1-dependent apoptosis and cell cycle entries.