Electronic Design Automation (EDA) tools have facilitated the design of ever more complex integrated circuits each year. Synthetic biology would also benefit from the development of Genetic Design Automation (GDA) tools. Existing GDA tools require biologists to design genetic circuits at the molecular level, roughly equivalent to designing electronic circuits at the layout level. Analysis of these circuits is also performed at this very low level. This thesis presents a first step at developing a GDA tool that supports higher levels of abstraction. In particular, this thesis describes the Genetic Circuit Model (GCM), a graphical specification language from which molecular descriptions can be synthesized. The GCM has several advantages. The input is tightly controlled through the use of an editor, limiting the possibility of user error. The representation of the genetic circuit is much more compact than using the System Biology Markup Language (SBML), the standard form for representing genetics circuits. The GCM can be automatically translated into SBML, allowing GCM’s to be easily simulated across multiple different simulators. The GCM to SBML translation process is targeted in such a way that the resulting output can be easily abstracted to allow for efficient simulation. To evaluate and test the GCM, this thesis presents a case study of the design of a genetic Muller C-element, a gate often used in asynchronous design. Three different genetic Muller C-elements are designed and analyzed. The utility of the GCM is demonstrated as it allows for efficient analysis of the Muller C-elements. The results of the simulations show that logically equivalent circuits can have different behaviors. In particular, a speed independent Muller C-element does not necessary imply that the gate is more robust than a non-speed independent gate. Design principles gathered from the simulations are that dual-rail outputs are essential, high gene count increases robustness, cooperativity greater than one is necessary, repression needs to be strong, and decay rates must be balanced for high robustness and low switching time. One potential application of the genetic Muller C-element is determining when to start the invasion of cancer cells. The two input signals are an environmental signal, and a communication signal. Using these signals, the bacteria colony can correctly reach consensus on when to begin the invasion. One interesting result is that noise is necessary in correctly switching into the invasion state.