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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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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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