We applied thermodynamic models, which exploit the tools of statistical mechanics, to compute the probability that RNA polymerase will be found at the appropriate promoter in bacteria. The models describe the interaction of repressors, activators, helper molecules and RNA polymerase with a number of well-characterized bacterial promoters. As a result we showed that thermodynamic models, by providing a framework to quantify vastly different forms of gene expression using a few parameters, set a conceptual scheme for understanding measurements, and more importantly, for suggesting new experiments.

Transcription factors modulate the probability of finding RNA polymerase bound to the promoter. By knowing their microscopic parameters the level of gene-expression when acting in a combinatorial manner can be predicted.