The ability to integrate logic, memory, and modular functionality into living systems is a fundamental goal of synthetic biology. The goal of this project is to expand upon the current scope of biological computation by constructing higher-order biological state machines capable of controlled, predictable differentiation, and to simultaneously develop deployable software that automates the design of the genetic circuits that may enable such computation. These circuits will employ the behavior of DNA recombinases, which may be ÒtriggeredÓ by a chemical input to either excise or invert DNA fragments. Ultimately, we hope to deploy our software as an available resource for synthetic biologists and to explore further avenues in biotechnology in which our constructs may be applied.

I have been working in the Lu Lab on the experimental aspects of this project since February 2014. Additionally, I have conducted research in cancer genomics in the Wang Lab at the USC Keck School of Medicine, where I applied bioinformatics methods for the analysis of DNA/RNA sequencing data from a glioblastoma patient.