Engineering Living Systems: Closing the Loop in the Design-Build-Test Cycle using the Semantic Web

Abstract

The cell can do many wondrous things: produce valuable chemical compounds, assemble beautiful structures, move with purpose, and process information. For the synthetic biologist, these behaviors might be programmed at a genetic level in order to yield useful applications in health, energy, and environment. However, these applications are still in their infancy and synthetic biology remains a very empirical science due to our limited ability to reliably predict how genetic systems behave. Moreover, synthetic biologists struggle to build off the work of their predecessors, as much valuable knowledge and experience gained in the laboratory is not easily shared or reproducible. To address these scientific challenges, I’ve developed computer-aided technologies, data exchange standards, and semantic web infrastructure that enable synthetic biologists to design, build, and test genetic systems on an industrial scale. In this dissertation, I highlight the fundamental engineering principles of standardization, modularity, and abstraction, and demonstrate how I am applying these principles in the fields of genetic engineering and synthetic biology.