Molecular imaging is already a powerful tool for investigating molecular interactions within the cell. Interpreting molecular imaging findings will, however, take us into the more unfamiliar, nonlinear realm of networks. The network class of interest is the “scale-free” network, which characterizes not only the cell, but also surprisingly, other real work networks such as the world wide web. This network topology yields insights in how the cell is functionally organized via motifs, modules, and different types of hubs. Additional organizational information is gained from the cell's evolutionary history. Interpretation of molecular images will be deepened by a both qualitative and quantitative knowledge of the cell's network. Importantly, cell network behavior can be independent of molecular detail. For this reason, the same molecule can serve different functions in different cells or even within the same cell. Since a scale-free network's behavior is likely to be nonlinear and exhibit emergent behavior, a degree of caution is prudent in assigning cause and effect to molecular imaging findings in our effort to reengineer some of the cell's functions. Molecular imagers will need to be cognizant of the level of organization in the cell's network they are interrogating.