One powerful approach to understanding how cells process spatially variant signals is based on using micropatterned substrates to control the distribution of signaling molecules. However, quantifying spatially complex signals requires an appropriate metric. Here we propose that the Shannon information theory formalism provides a robust and useful way to quantify the organization of proteins in micropatterned systems. To demonstrate the use of informational entropy as a metric, we produced patterns of lines of fibronectin with varying information content. Fibroblasts grown on these patterns were sensitive to very small changes in informational entropy (6.6 bits), and the responses depended on the scale of the pattern.