CIDAR Lab does active research in multiple domains related to Synthetic Biology. Here are some publications that can help orient you to the various research topics.

Our Papers:

Two concise visions for the computational side of synthetic biology.

D. M. Densmore and S. Bhatia, “Bio-design automation: software + biology + robots,” Trends in Biotechnology, vol. 32, iss. 3, pp. 111-113, 2014.doi:10.1016/j.tibtech.2013.10.005.

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

Other Papers:

Good explanation of engineering foundations and the associated goals for synthetic biology, and a fairly up-to-date history of synthetic biology as a field.

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.

Our Papers:

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): aac7341.

his paper describes Cello- a popular computational framework to synthesize genetic logic circuits using Verilog HDL for functional specification of the circuit. The paper has a good mix of Computational and Biological applications of BioDesign Automation.

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

This paper explores the computational algorithms of Raven, a software tool to assist and automate the generation of instructions of assembly algorithms to clone genetic components in a biological lab.

Other Papers:

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.

Simulation is a very important aspect of BioDesign Automation to help predict the functional behavior of genetic components based on their biochemical mechanisms. iBioSim is one of the pioneers of simulation in SynBio and is widely used by groups including CIDAR Lab.

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): gks531.

Like Clotho and SBOL Stack, ICE is a popular biological part repository and a good example for a widely used DBMS in Synbio.

Our Papers:

N. Roehner, J. Beal, K. Clancy, B. Bartley, G. Misirli, R. Gruenberg, E. Oberortner, M. Pocock, M. Bissell, C. Madsen, T. Nguyen, M. Zhang, Z. Zhang, Z. Zundel, D. Densmore, J. Gennari, A. Wipat, H. Sauro, and C. J. Myers, “Sharing Structure and Function in Biological Design with SBOL 2.0,” ACS Synthetic Biology, 2016. doi:10.1021/acssynbio.5b00215

Shows a good example of exchanging genetic designs using multiple BDA tools from different institutions.

P. Vaidyanathan, B. S. Der, S. Bhatia, N. Roehner, R. Silva, C. A. Voigt, and D. Densmore, “A Framework for Genetic Logic Synthesis,” Proceedings of the IEEE, vol. 103, iss. 11, pp. 2196-2207, 2015. doi:10.1109/JPROC.2015.2443832

Describes details of how to build up a framework for performing genetic logic synthesis along with some examples.

Other Papers:

M. W. Lux, B. W. Bramlett, D. A. Ball, and J. Peccoud, “Genetic design automation: engineering fantasy or scientific renewal?,” Trends in Biotechnology, Volume 30, Issue 2, February 2012, Pages 120-126, ISSN 0167-7799. doi:10.1016/j.tibtech.2011.09.001

This paper talks about some of the challenges in BDA and gives some thoughts on how to address them.

E. Oberortner, J. Cheng, N. J. Hillson, and S. Deutsch, “Streamlining the Design-to-Build Transition with Build-Optimization Software Tools,” ACS Synthetic Biology, 2016. doi:10.1021/acssynbio.6b00200

This paper shows an example of an entire BDA workflow.

Other Papers:

Zhu, Pingan, and Liqiu Wang. “Passive and active droplet generation with microfluidics: a review.” Lab on a Chip 17.1 (2017): 34-75.

This paper is  a good recent review on droplet microfluidics.

Kintses, Balint, et al. “Picoliter cell lysate assays in microfluidic droplet compartments for directed enzyme evolution.” Chemistry & biology 19.8 (2012): 1001-1009.

This paper discusses the application of droplet microfluidics in directed evolution with cell-free assays.

Other Papers:

Thorsen, Todd, Sebastian J. Maerkl, and Stephen R. Quake. “Microfluidic Large-Scale Integration.” Science 298, no. 5593 (October 18, 2002): 580–84. doi:10.1126/science.1076996.

This paper demonstrates the necessity for Computer Automated Design Tools for Microfluidics.

Araci, Ismail Emre, and Philip Brisk. “Recent Developments in Microfluidic Large Scale Integration.” Current Opinion in Biotechnology, Analytical biotechnology, 25 (February 2014): 60–68. doi:10.1016/j.copbio.2013.08.014.

This paper gives a good overview of the current state of Microfluidics CAD Software

Our Papers:

Silva, Ryan, Swapnil Bhatia, and Douglas Densmore. “A reconfigurable continuous-flow fluidic routing fabric using a modular, scalable primitive.” Lab on a Chip 16.14 (2016): 2730-2741.

The transposer framework emphasizes CIDAR’s ability to quickly design, build and test novel microfluidic primitives and scale them in such a manner that would be extremely difficult in the absence of automation.

Huang, Haiyao, and Douglas Densmore. “Integration of microfluidics into the synthetic biology design flow.” Lab on a Chip 14.18 (2014): 3459-3474.

This review article effectively enumerates the significant benefits microfluidics can offer the synthetic biology community through a wide range of case studies and potential advancements.

Other Papers:

Tamsir, Alvin, Jeffrey J. Tabor, and Christopher A. Voigt. “Robust multicellular computing using genetically encoded NOR gates and chemical/wires/‘.” Nature 469.7329 (2011): 212-215.

This paper was one of the fundamental advancements that birthed the Fluigi project. The idea of scaling a multicellular network in a microfluidic towards producing higher-order biological feedback mechanisms is a problem that inherently requires software in order to manage complexity.

Guckenberger, David J., et al. “Micromilling: a method for ultra-rapid prototyping of plastic microfluidic devices.” Lab on a Chip 15.11 (2015): 2364-2378.

This paper outlines the challenges and benefits of using a CNC mill to fabricate microfluidics.