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The circuit design uses an externally applied ligand that activates a computationally designed transcriptional response driven by a tissue specific promoter to control output (GFP expression). In addition, I engineered a circuit that adds a positive feedback motif. To quantify the behaviors of these circuits I developed a MATLAB program to remove background signals from confocal microscopy images and quantify GFP signal in a high-throughput manner. The genetic circuit is highly specific for root epidermal cells, controllable with external ligand, and has increased sensitivity and memory with positive feedback. The concepts and components of these circuits can be implemented in future designs to engineer and produce plants with more predictable and diverse behaviors affording the operator greater control.","abstract_html":"Synthetic biologists aim to rationally design genetic circuits and utilize plant platforms to photosynthetically drive, self-sustainable circuits. Although plants are excellent platforms, issues and unpredictability arise from the innate complexity of multicellularity. The ability to quantitatively control gene expression within specific cell types can address some issues arising from multicellularity. In my research, I developed a genetic circuit with the ability to induce and quantitatively control expression in Arabidopsis thaliana root epidermal cells. The circuit design uses an externally applied ligand that activates a computationally designed transcriptional response driven by a tissue specific promoter to control output (GFP expression). In addition, I engineered a circuit that adds a positive feedback motif. To quantify the behaviors of these circuits I developed a MATLAB program to remove background signals from confocal microscopy images and quantify GFP signal in a high-throughput manner. 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