The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A Synthetic Genetic Edge Detection Program
Open accessAbstract
Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.
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Cites
Foundations for engineering biology
Endy, D. (2005) · Nature · doi:10.1038/nature04342 · Cited by 1,511
Characterization of the reconstructed 1918 Spanish influenza pandemic virus
Tumpey, T. M., Basler, C. F., Aguilar, P. V., Zeng, H., Solórzano, A., Swayne, D. E., Cox, N. J., Katz, J. M., Taubenberger, J. K., Palese, P., et al. (2005) · Science · doi:10.1126/science.1119392 · Cited by 1,327
The second wave of synthetic biology: from modules to systems
Purnick, P. E. M., & Weiss, R. (2009) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2698 · Cited by 1,181
Cello, J., Paul, A. V., & Wimmer, E. (2002) · Science · doi:10.1126/science.1072266 · Cited by 980
Benner, S. A., & Sismour, A. M. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1637 · Cited by 834
Quantitative model for gene regulation by lambda phage repressor.
Ackers, G. K., Johnson, A. D., & Shea, M. A. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.4.1129 · Cited by 590
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Salis, H. M., Mirsky, E. A., & Voigt, C. A. (2009) · Nature Biotechnology · doi:10.1038/nbt.1568 · Cited by 1,844
Self-citationSynthetic biology: applications come of age
Khalil, A. S., & Collins, J. J. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2775 · Cited by 1,373
A synchronized quorum of genetic clocks
Danino, T., Mondragón-Palomino, O., Tsimring, L., & Hasty, J. (2010) · Nature · doi:10.1038/nature08753 · Cited by 992
A brief history of synthetic biology
Cameron, D. E., Bashor, C. J., & Collins, J. J. (2014) · Nature Reviews Microbiology · doi:10.1038/nrmicro3239 · Cited by 933
Engineering Stem Cell Organoids
Yin, X., Mead, B. E., Safaee, H., Langer, R., Karp, J. M., & Levy, O. (2016) · Cell Stem Cell · doi:10.1016/j.stem.2015.12.005 · Cited by 866
Metadata
- Authors
- Tabor, J. J., Salis, H. M., Simpson, Z. B., Chevalier, A. A., Levskaya, A., Marcotte, E. M., Voigt, C. A., & Ellington, A. D.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2009-06
- Volume
- 137
- Issue
- 7
- Pages
- 1272-1281
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2099090468
- Cited by
- 488
- References
- 6
- FWCI
- 13.32
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Tabor, J. J., Salis, H. M., Simpson, Z. B., Chevalier, A. A., Levskaya, A., Marcotte, E. M., Voigt, C. A., & Ellington, A. D. (2009). A Synthetic Genetic Edge Detection Program. Cell. https://doi.org/10.1016/j.cell.2009.04.048
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