Gene regulation networks (GRNs) are essential for the processing of information that cells are receive continuously. One important example occurs during development of multicellular organisms in which GRNs are crucial for patterning bodies. Surprisingly, similar body plans can be driven by very different GRNs. We study how these different solutions work, how they evolved and whether some are more robust than others. These are central questions in modern biological research and therefore they have obtained a lot of attention, much of it in the context of whole organisms. In contrast, we use synthetic biology to gain insight into these questions through a novel “bottom-up” approach by creating simple, de novo gene regulatory networks. We aim to understand the fundamental design principles of networks that map genotypes into phenotypes by studying these synthetic networks. We do this by combining wet lab experiments (including microfluidic techniques) and computational modelling.