Complex biological behaviors are encoded in the DNA sequences of regions that control gene activity. Advances in our understanding of these behaviors have been gained recently by quantitative models that describe how DNA-binding molecules interact with the genomic sequence. An emerging view is that every control sequence is associated with a unique binding affinity landscape for each molecule and consequently, with a unique set of molecule binding configurations and activation outputs. I will present a probabilistic framework based on the hypothesis of competitive binding equilibrium that unifies these ideas, and show that it explains several experimental observations regarding binding patterns of molecules, and dynamics of gene activation. The framework can also be used to model more complex phenomena such as noise in gene activation and the evolution of gene activity control.