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Research Overview

CIDAR research is focused on the application of design automation techniques to the creation of synthetic biological systems, microfluidics, and cyber-physical systems. In particular, the work of the group enables specify, design, build, test, learn workflows that use novel combinations of software, hardware, and microbiology (wetware). These systems often take high level descriptions and transform them into either collections of well understood DNA or microfluidic components. While largely application agnostic, our lab does focus on bio-sensors and replication of computational paradigms in biology such as computation, communication, and coordinated networks of living systems. 

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Synthetic Biology

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Microfluidics

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Cyber-Physical Systems 

Synthetic Biology is the forward engineering of novel living systems. CIDAR specifically enables workflows that take abstract functional, structural, or performance specifications and transform them into collections of well understood DNA elements that can be introduced into living systems to perform computation, create materials, or produce therapeutics.  An excellent example of our approach is NSF's Living Computing Project.

Low-cost, continuous flow microfluidics are unnecessarily complicated in their design and operation. CIDAR creates software tools and manufacturing processes to create microfludics that can be manufactured in hours, by non-experts, inexpensively.  These devices can now serve as hybrid bio-electronic interfaces that allow bio-sensing systems to communicate and process data electronically.

Cyber-Physical systems in CIDAR emcompasses both the interaction of our systems with the environment as well as development of high-throughput, semi-autonomous laboratory environments. These environments allow not only for remote software to submit jobs to create new living systems but allow for existing processing to be more less error prone and more replicable. 

Curated collections of papers that will help you understand more about the research and problems we are trying to solve

Synthetic Biology Overview

  • D. M. Densmore and S. Bhatia, “Bio-design automation: software + biology + robots,” Trends in Biotechnology, vol. 32, iss. 3, pp. 111-113, 2014.

  • D. Densmore, “Bio-Design Automation: Nobody Said It Would Be Easy,” ACS Synthetic Biology, vol. 1, iss. 8, pp. 296-296, 2012.

  • D. Endy, “Foundations for engineering biology,” Nature, vol. 438, pp. 449-453, 2005.

  • D. E. Cameron, C. J. Bashor, and J. J. Collins, “A brief history of synthetic biology,” Nat Rev Microbiol, vol. 12, pp. 381-390, 2014.

BDA Software and Applications

  • Nielsen, Alec AK, Bryan S. Der, Jonghyeon Shin, Prashant Vaidyanathan, Vanya Paralanov, Elizabeth A. Strychalski, David Ross, Douglas Densmore, and Christopher A. Voigt. “Genetic circuit design automation.” Science 352, no. 6281 (2016).

  • Appleton, Evan, Jenhan Tao, Traci Haddock, and Douglas Densmore. “Interactive assembly algorithms for molecular cloning.” Nat. Methods 11 (2014): 657-662.

  • Myers, Chris J., Nathan Barker, Kevin Jones, Hiroyuki Kuwahara, Curtis Madsen, and Nam-Phuong D. Nguyen. “iBioSim: a tool for the analysis and design of genetic circuits.” Bioinformatics 25, no. 21 (2009): 2848-2849.

  • Ham, Timothy S., Zinovii Dmytriv, Hector Plahar, Joanna Chen, Nathan J. Hillson, and Jay D. Keasling. “Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools.” Nucleic acids research (2012).

Microfluidics Hardware, Software, and Application

  • H. Huang and D. Densmore, “Fluigi: Microfluidic Device Synthesis for Synthetic Biology,” J. Emerg. Technol. Comput. Syst. Special Issue on Synthetic Biology, vol. 11, iss. 3, p. 26:1–26:19, 2014.

  • R. Silva, S. Bhatia, and D. Densmore, “A reconfigurable continuous-flow fluidic routing fabric using a modular, scalable primitive,” Lab Chip, vol. 16, pp. 2730-2741, 2016.

  • A. Lashkaripour, R. Silva, and D. Densmore, “Desktop micromilled microfluidics,” Microfluidics and Nanofluidics, vol. 22, iss. 3, p. 31, 2018.

  • Lashkaripour, Ali, Christopher Rodriguez, Luis Ortiz, and Douglas Densmore. “Performance Tuning of Microfluidic Flow-Focusing Droplet Generators.” Lab on a Chip 19, no. 6 (March 13, 2019): 1041–53

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