Modeling transcriptional regulation using thermo-dynamic modeling approaches has become increasingly relevant as a way to gain a detailed understanding of transcriptional regulation. Thermodynamic models are able to model the interactions between transcription factors (TFs) and DNA that lead to a specific transcriptional output of the target gene. Such models can be trained by fitting their free parameters to data on the transcription rate of a gene and the concentrations of its regulating factors. However, the parameter fitting process is computationally very expensive and this limits the number of alternative types of model that can be explored.