Programming Biology

Computing in the 21st century is extremely exciting, diverse, and democratized. Using just a few simple concepts and a personal computer, people of all ages and backgrounds can create smartphone applications, social media networks, and amazing electronic gadgets. Each of these creations can then be shared, modified, and extended by others. This project is going to let us “program biology” and democratize the process as society has with electronic computing. Programming biology is going to be the key to solving many of the 21st century’s most pressing human health, agricultural, and materials challenges.

This project’s technology will allow us to apply the same simple concepts from traditional computing and use them to design new solutions in bio-therapeutics, bio-materials, bio-energy, and bio-remediation. Programming biology will allow for amazing systems that can harness evolution, adaptation, replication, self-repair, chemistry, and living organisms. This project will create a quantitative set of freely available design principles, computational tools, mathematical models, physical biological artifacts, educational resources, and outreach activities. Once available, these resources will allow for novel, living biological solutions to be built more quickly, perform better, be more reliable to manufacture, and cost less to produce.

This project is unique in that these resources will be explicitly developed to validate key computational concepts to understand how well these concepts can be applied rigorously and repeatedly to biology. This project decomposes these concepts into three areas: Computing Paradigm (digital, analog, memory, and communication), Computing Activity (specification, design, and verification), and Computing Metric (time, space, quality, and complexity). Once complete, this project will provide the most comprehensive, freely available, and computationally relevant set of building blocks to engineer biological systems to date.

Scientific Work

Explicitly five unanswered questions will be addressed in this project:

  • What computational models are available to biology, what are their limits, and how do they perform?
  • What communication mechanisms are available to biology, what are their limits, and how do they perform?
  • What are the theoretical and empirical measures of quality, scale, time, and space in biological computing systems?
  • How generalizable are the concepts and “design rules” which can be learned from studying biological systems?
  • How can the results (data and learnings) from biological specification, design, and verification be authoritatively disseminated to the community as design principles and grand challenges?

This project addresses these questions with an interdisciplinary team with expertise in theoretical computer science, electronic design automation, bio-physics/chemistry, control theory, and molecular cell biology. We will approach this project by building individual DNA “parts”, quantitatively measuring their individual performance, and rigorously testing their limits regarding compositional structure, performance, and function. We will then archive these building blocks and associated data in an open source data repository. In addition, software tools will be created that let others use these parts effectively. We will investigate using these parts in the development of bio-sensing and cell-differentiation/detection applications. We will develop a “roadmap” that helps the field chart the predicted future applicability of this technology.

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Our Team

Douglas Densmore (Lead PI)
Associate Professor; Department of Electrical and Computer Engineering
Boston University
dougd@bu.edu
http://cidarlab.org

Swapnil Bhatia
Research Assistant Professor; Department of Electrical and Computer Engineering
Boston University
swapnilb@bu.edu
http://people.bu.edu/swapnilb/

Ahmad “Mo” Khalil
Assistant Professor; Biomedical Engineering Department
Boston University
akhalil@bu.edu
http://www.bu.edu/khalillab/

Wilson Wong
Assistant Professor; Biomedical Engineering Department
Boston University
wilwong@bu.edu
http://wilsonwonglab.org

Domitilla Del Vecchio
Associate Professor; Department of Mechanical Engineering
MIT
ddv@mit.edu
http://www.mit.edu/~ddv/

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Tim Lu
Associate Professor; Department of Electrical Engineering and Computer Science
MIT
timlu@mit.edu
http://www.rle.mit.edu/sbg/

Christopher Voigt
Professor; Biological Engineering Department
MIT
cavoigt@gmail.com
http://web.mit.edu/voigtlab/

Ron Weiss
Professor; Biological Engineering Department
MIT
rweiss@mit.edu
http://groups.csail.mit.edu/synbio/

Pete Carr
Senior Scientist
MIT Lincoln Labs
carr@ll.mit.edu
https://synbio.mit.edu/members/faculty/peter-carr

Jacob Beal
Scientist
BBN Technologies
jakebeal@bbn.com
http://openmap.bbn.com/~jbeal/

Sponsored by National Science Foundation’s Expeditions in Computing Program (Award #1522074)