Considerable attention has been directed in recent years toward the development of methods for the contextual analysis of expression data using interaction networks. Of particular interest has been the identification of active subnetworks by detecting regions enriched with differential expression. In contrast, however, very little effort has been made toward the application of comparable methods to other types of high-throughput data.