The flow of information through a biological network can greatly influence the operation and behavior of the system. Quantitative analysis of these properties is often difficult in naturally occurring systems, but can be greatly facilitated by studying simple synthetic networks. Here we present synthetic transcriptional cascades of various length and study their dynamic and steady state behavior both experimentally and through a stochastic model. These systems enable us to analyze sensitivity and noise propagation as a function of network complexity.