The quantitative relation between transcription factor concentrations and the rate of protein production from downstream genes is central to the function of genetic networks. I will describe a technique to measure this relation, the gene regulation function, in individual living cells. The gene regulation function is often a sigmoidal function, and I will show that, by interpreting genetic networks as inference modules, we can make predictions about why this sigmoidal function has different characteristics for different genetic networks. Our results should provide a basis for both understanding cellular decision-making and for designing synthetic genetic circuits.