The advent of high throughput techniques and genome sequencing brought about a new era in the availability of biological data. This created a need for new approaches for data integration and interpretation. It is becoming clear that signalling pathways are integrated into a complex network and the human brain cannot handle this complexity. This requires a more quantititative approach to the analysis of how such systems work, but many current experimental techniques are poorly quantitative and the data are not easily integrated together. Systems biology seeks to solve some of these problems by applying multidisciplinary experimental and theoretical approaches to analyse and understand biological systems. The experimental and theoretical approaches need to be appropriate for the task. It is important to be able to analyse enough components in order to be able to understand the function of the whole system. Research scientists need to be trained to communicate with people from other disciplines. I will discuss how these hurdles may be overcome. My talk will use examples from analysis of the NF-kappaB system and prolactin gene expression. Nuclear Factor kappa B (NF-kappaB) regulates cellular stress responses and the immune response to infection. We used an integrated live cell imaging and mathematical approach to analyse this system. We found that NF-kappaB activation results in oscillations in nuclear NF-kappaB abundance1. We found that the timing of the oscillations regulates downstream gene expression2. I will show how the use of modelling has made unexpected insights into how this system works. Finally, I will go on to discuss new approaches for the analysis of transcriptional variation in live cells.