The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Programmable chemical controllers made from DNA
Open accessAbstract
Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language', and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.
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Cites
Design and self-assembly of two-dimensional DNA crystals
Winfree, E., Liu, F., Wenzler, L. A., & Seeman, N. C. (1998) · Nature · doi:10.1038/28998 · Cited by 2,857 · cited 1×
“DNA nanotechnology (4, 5) is in a unique position among the many actively pursued strategies for constructing molecular nano-robots, demonstrating progress towards the rational design of all the required elements: sensors and amplifiers (6–11), circuits (12–25), motors (26–30), and structures (4, 31, 32).”
BackgroundThe cultural niche: Why social learning is essential for human adaptation
Boyd, R., Richerson, P. J., & Henrich, J. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1100290108 · Cited by 1,303
The cultural evolution of emergent group-level traits
Smaldino, P. E. (2014) · Behavioral and Brain Sciences · doi:10.1017/s0140525x13001544 · Cited by 211
Cited by
DNA nanotechnology from the test tube to the cell
Chen, Y.-J., Groves, B., Muscat, R. A., & Seelig, G. (2015) · Nature Nanotechnology · doi:10.1038/nnano.2015.195 · Cited by 594
Self-citationMaterials learning from life: concepts for active, adaptive and autonomous molecular systems
Merindol, R., & Walther, A. (2017) · Chemical Society Reviews · doi:10.1039/c6cs00738d · Cited by 533
Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks
Cherry, K. M., & Qian, L. (2018) · Nature · doi:10.1038/s41586-018-0289-6 · Cited by 486
Computing in mammalian cells with nucleic acid strand exchange
Groves, B., Chen, Y.-J., Zurla, C., Pochekailov, S., Kirschman, J. L., Santangelo, P. J., & Seelig, G. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2015.278 · Cited by 220
Self-citationMultifunctional sequence-defined macromolecules for chemical data storage.
Martens, S., Landuyt, A., Espeel, P., Devreese, B., Dawyndt, P., & Du Prez, F. (2018) · Nature Communications · doi:10.1038/s41467-018-06926-3 · Cited by 180
Metadata
- Authors
- Chen, Y.-J., Dalchau, N., Srinivas, N., Phillips, A., Cardelli, L., Soloveichik, D., & Seelig, G.
- Venue
- Nature Nanotechnology
- Published
- 2013-09-29
- Volume
- 8
- Issue
- 10
- Pages
- 755-762
- ISSN
- 1748-3387 (ISSN-L)
- 1748-3395
- OpenAlex
- W1990476699
- Cited by
- 486
- References
- 3
- FWCI
- 17.62
- Type
- journal article
- Language
- en
- Open access
- green
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