L. You
Duke University,
United States
Keywords: synthetic biology, deep learning, living materials
Summary:
The ability to program complex self-organized patterns in living cells has profound implications for both a basic understanding of pattern formation in nature and for diverse future applications. These applications include the living fabrication of functional materials, information encoding and decoding, and distributed computation. Despite nearly two decades of efforts in synthetic biology, however, the progress in programming self-organized patterns has been limited, in comparison with other types of dynamics. To this end, our lab has been integrating mathematical modeling, machine learning, and quantitative experiments to achieve predictable programming of self-organized patterns in bacteria. In this presentation, I will discuss our recent efforts and progress in this line of research.