Gene expression is often maintained by a complex network of cross-regulatory interactions. In this talk I will focus on the segment polarity genes of Drosophila melanogaster, and the network of interactions determining the stability of their expression. I will present a Boolean representation of this network that assumes that genes and proteins are either ON or OFF, and their interactions can be formulated as logical functions. This simple model is able to reproduce the wild type expression obtained for gene mutation experiments. In addition, the Boolean representation allows for a more complete analysis of the possible steady states as experiments, and for a better identification of the initial conditions that lead to certain steady states. I propose this type of analysis as a first, qualitative step in understanding complex networks. The success of a Boolean representation strongly suggests that the topology of the network is correctly taken into account, and a more quantitative approach can be used.