Using mathematical toolkits traditionally considered the property of statistical physics and artificial intelligence, researchers have developed a way to identify important cancer mutations. This approach can model the effects that cancer mutations have on the intricate patterns of communication between groups of proteins involved in cell signaling. The model shows how mutations can alter signaling networks and points the way to a better understanding of cancer genomes.