Biological networks are the representation of multiple interactions within a cell, a global view intended to help understand how relationships between molecules dictate cellular behavior. Recent advances in molecular and computational biology have made possible the study of intricate transcriptional regulatory networks that describe gene expression as a function of regulatory inputs specified by interactions between proteins and DNA. Here we review the properties of transcriptional regulatory networks and the rapidly evolving approaches that will enable the elucidation of their structure and dynamic behavior. Several recent studies illustrate how complementary approaches combine chromatin immunoprecipitation (ChIP)-on-chip, gene expression profiling, and computational methods to construct blueprints for the initiation and maintenance of complex cellular processes, including cell cycle progression, growth arrest, and differentiation. These approaches should allow us to elucidate complete transcriptional regulatory codes for yeast as well as mammalian cells.