Research Interests: biological systems; synthetic biology; pattern generation
I am a graduate student pursuing a PhD at UC Berkeley in the EECS department working with Murat Arcak in the Networked Dynamical Systems Group (NDSG). I have B.S. degrees in EECS and Mechanical Engineering and an M.S. degree in EECS, all from UC Berkeley.
Synthetic Turing Patterns [BPN518]
Understanding symmetry breaking is at the heart of developmental biology, from the origins of polarity, cellular differentiations, and how the leopard got its spots, as well as crucial to the future engineering of complex cellular ensembles. Alan Turing proposed a simple mathematical model that explains how the reaction-diffusion mechanism can cause an initially uniform concentration in an ensemble of cells to spontaneously become non-uniform and form patterns (Turing patterns). To date, no true synthetic Turing patterns have been created using gene networks, so our goal is to design and implement the first synthetic gene circuit that can spontaneously produce patterning via diffusion-driven instability in an ensemble of cells (E. coli). In addition, the main engine driving Turing pattern formation is a robust nonlinear circuit, such as a bistable or oscillatory network. Creating these nonlinear circuits will be beneficial both as a major step in the eventual creation of Turing pattern generators as well as modular circuits for synthetic biology.