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Diverse and robust molecular algorithms using reprogrammable DNA self-assembly
Abstract
Molecular biology provides an inspiring proof-of-principle that chemical systems can store and process information to direct molecular activities such as the fabrication of complex structures from molecular components. To develop information-based chemistry as a technology for programming matter to function in ways not seen in biological systems, it is necessary to understand how molecular interactions can encode and execute algorithms. The self-assembly of relatively simple units into complex products 1 is particularly well suited for such investigations. Theory that combines mathematical tiling and statistical-mechanical models of molecular crystallization has shown that algorithmic behaviour can be embedded within molecular self-assembly processes 2,3, and this has been experimentally demonstrated using DNA nanotechnology 4 with up to 22 tile types 5-11. However, many information technologies exhibit a complexity threshold-such as the minimum transistor count needed for a general-purpose computer-beyond which the power of a reprogrammable system increases qualitatively, and it has been unclear whether the biophysics of DNA self-assembly allows that threshold to be exceeded. Here we report the design and experimental validation of a DNA tile set that contains 355 single-stranded tiles and can, through simple tile selection, be reprogrammed to implement a wide variety of 6-bit algorithms. We use this set to construct 21 circuits that execute algorithms including copying, sorting, recognizing palindromes and multiples of 3, random walking, obtaining an unbiased choice from a biased random source, electing a leader, simulating cellular automata, generating deterministic and randomized patterns, and counting to 63, with an overall per-tile error rate of less than 1 in 3,000. These findings suggest that molecular self-assembly could be a reliable algorithmic component within programmable chemical systems. The development of molecular machines that are reprogrammable-at a high level of abstraction and thus without requiring knowledge of the underlying physics-will establish a creative space in which molecular programmers can flourish.
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“Past applications of this idea include the design of a set of TX tiles that carry out a cumulative XOR operation, a set of DX tiles that self-assemble into a Sierpinski triangle, and impressively, a set of 355 SSTs that can be used to produce a variety of cellular automata capable of carrying out a number of computational tasks (Figure 11).144”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [144]
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“Particularly interesting in the latter example is the ability to controllably reintroduce indeterminism by including a plurality of tiles that could fill a given niche and leaving the ultimately realized pattern up to competition.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [144]
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Self-citation
Metadata
- Authors
- Woods, D., Doty, D., Myhrvold, C., Hui, J., Zhou, F., Yin, P., & Winfree, E.
- Affiliations
- California Institute of Technology (US)
- Harvard University (US)
- Corresponding author
- Woods, Damien
- Doty, David
- Winfree, Erik
- Venue
- Nature
- Published
- 2019-03
- Volume
- 567
- Issue
- 7748
- Pages
- 366-372
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2924487690
- Cited by
- 295
- References
- 36
- Citations by year
- 2026: 22 · 2025: 38 · 2024: 35 · 2023: 49 · 2022: 47 · 2021: 50 · 2020: 36 · 2019: 18
- FWCI
- 12.50
- Type
- journal article
- Language
- en
- Update notices
- correction (2019-08-02)
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Maynooth University ePrints and eTheses Archive (Maynooth University) (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Theoretical Computer Science › DNA and Biological Computing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
- Keywords
- DNA self-assembly, DNA nanotechnology, algorithmic self-assembly, sorting algorithms, cellular automata simulation, leader election, counting, error rate
- MeSH terms
- Algorithms, DNA, Reproducibility of Results, Nanotechnology
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