Individual transcription factors often regulate multiple genes in an organism. For these transcription factors with broad regulatory effects, the number of individual transcription factor proteins in the cells at a given time can be less than the total number of binding sites in the genome. When transcription factors are limited, those binding sites with the strongest affinity are likely to be occupied first. Only when the transcription factor is in excess would the weakest binding sites by occupied. This “molecular titration” effect suggests that the distribution of binding site affinities throughout the genome contributes to setting the timing of gene activation. Earlier work in V. harveyi explore how differences in transcription factor binding energies contributed to the queing of gene expression in quorum sensing. Here we present experimental and theoretical work to quantitatively predict how variability in transcription factor binding site strengths in the genome encode for the ordering and dynamics of gene expression.In our study, we set out to resolve the time lag between genes regulated by a single transcription factor. We use a model system implementing the LuxR/LuxI quorum sensing network to measure the time lag between expression of genes regulated by strong and weak LuxR binding sites. A model that uses statistical mechanics to predict operator occupancy was derived to predict how the number and distribution of operator strengths throughout the genome set the timing of gene activation. This increased understanding of expression dynamics gives us another tool to program temporal patterns of expression into microbes as well as understand how the dynamics of microbial activity is encoded in natural genomes.