Our project aimed to enhance the integration of novel methodologies and algorithms within comprehensive workflows for genetic design automation. By employing sophisticated thermodynamic models of promoter behavior, we investigated the impact of cellular context effects, specifically addressing crosstalk resulting from regulator specificity limitations and the titration of circuit regulators binding to off-target sites on the host genome. To manage the resultant computational complexity, we implemented dedicated branch-and-bound techniques during technology mapping. Through a case study involving the synthesis of combinational logic circuits utilizing a previously published device library (Cello), we analyzed the ramifications of varying degrees and distributions of crosstalk on circuit performance and library usability. Additionally, we proposed a model for non-equilibrium steady-state gene expression, capable of predicting protein count distributions and associated energy consumption rates in response to transcription factor inputs. This model's adaptability to diverse scenarios, including multiple transcription factor binding sites, distinct transcription factor species, and variable transcription rates, facilitates its application across different organisms and levels of abstraction. Leveraging our model, we enable energy-conscious technology mapping for genetic logic circuits, integrating function and energy expenditure optimization through constrained or multi-objective optimization approaches. Moreover, we devised strategies to enhance search space exploration efficiency concerning structural variants.
