Beginning an ambitious (NSF) Expedition: Evolvable Living Computing

Today the official announcement is out and I can finally talk openly about what I've known for nearly two months now: we are beginning a major new synthetic biology project in partnership with Boston University and MIT, led by Doug Densmore over at BU.  "Evolvable Living Computing" is an NSF Expeditions in Computing project, a class of large-scale long-term basic research project that puts $10 million dollars into focused research on a deep challenge.

In the case of our project, that challenge is the computational side of synthetic biology.  Our goal, over the next few years, is to create the intellectual and scientific foundations for truly general computation in biological organisms.  Computation has long been an important goal in synthetic biology, dating back at least to the 1997 "Cellular Gate Technology" paper by Tom Knight and Gerry Sussman.  This vision has been elusive, however, partly because much of the funding available has been heavily focused on applications rather than foundations, and partly because we are only now beginning to overcome barriers to effective design design methods and develop metrics that accurately assess the computational power of biological devices.

In this project, we will be tackling those issues head-on, directly tackling the questions of performance, limitations, and scope of various biological computation models.  BBN's anticipated role in the project is foundations for the foundations, and I am excited to be funded on these works:

• First, I am in charge of connecting the work in the project to ongoing standards development efforts, including design representation with Synthetic Biology Open Language (SBOL) and measurement protocols being developed under the auspices of the NIST Synthetic Biology Standards Consortium.  
• Second, I will be working to make our flow cytometry analytics methods more widely available and effective, first within the project and then to the broader community as well.
• Finally, I will be extending the modeling, analysis, and design methods that we have developed for doing high-precision predictions and quantification of device performance, and creating libraries of high-performance biological computing devices.

I expect that this will be an exciting several years indeed, and hope to build off this foundation in many new directions and collaborations.