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 DNA tile self-assembly include TX tiles carrying out a cumulative XOR operation, DX tiles self-assembling into a Sierpinski triangle, and 355 SSTs producing cellular automata capable of computational tasks.
“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]
In the 355 SST example, indeterminism can be controllably reintroduced by including a plurality of tiles that could fill a given niche and leaving the ultimately realized pattern up to competition.
“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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Cites
Whitesides, G. M., & Grzybowski, B. A. (2002) · Science · doi:10.1126/science.1070821 · Cited by 7,457 · see citing works
Folding DNA to create nanoscale shapes and patterns
Rothemund, P. W. K. (2006) · Nature · doi:10.1038/nature04586 · Cited by 7,320 · see citing works
Lorenz, R., Bernhart, S. H., Höner zu Siederdissen, C., Tafer, H., Flamm, C., Stadler, P. F., & Hofacker, I. L. (2011) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-6-26 · Cited by 5,098 · see citing works
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 · see citing works
Self-citationSeeman, N. C., & Sleiman, H. F. (2017) · Nature Reviews Materials · doi:10.1038/natrevmats.2017.68 · Cited by 1,875 · see citing works
NUPACK: Analysis and design of nucleic acid systems
Zadeh, J. N., Steenberg, C. D., Bois, J. S., Wolfe, B. R., Pierce, M. B., Khan, A. R., Dirks, R. M., & Pierce, N. A. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21596 · Cited by 1,670 · see citing works
Complex shapes self-assembled from single-stranded DNA tiles
Wei, B., Dai, M., & Yin, P. (2012) · Nature · doi:10.1038/nature11075 · Cited by 992 · see citing works
Self-citationAlgorithmic Self-Assembly of DNA Sierpinski Triangles
Rothemund, P. W. K., Papadakis, N., & Winfree, E. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020424 · Cited by 860 · see citing works
Self-citationLogical computation using algorithmic self-assembly of DNA triple-crossover molecules
Mao, C., LaBean, T. H., Reif, J. H., & Seeman, N. C. (2000) · Nature · doi:10.1038/35035038 · Cited by 779 · see citing works
Universality in Elementary Cellular Automata
Cook, M. (2004) · Complex Systems · doi:10.25088/complexsystems.15.1.1 · Cited by 758 · see citing works
Programming DNA Tube Circumferences
Yin, P., Hariadi, R. F., Sahu, S., Choi, H. M. T., Park, S. H., LaBean, T. H., & Reif, J. H. (2008) · Science · doi:10.1126/science.1157312 · Cited by 486 · see citing works
Self-citationGenetic takeover and the mineral origins of life
Cairns-Smith, A. G. (1982) · Medical Entomology and Zoology · Cited by 433 · see citing works
The program-size complexity of self-assembled squares (extended abstract)
Rothemund, P. W. K., & Winfree, E. (2000) · ACM Symposium on Theory of Computing (STOC) · doi:10.1145/335305.335358 · Cited by 411 · see citing works
Self-citationProgrammable self-assembly of three-dimensional nanostructures from 10,000 unique components
Ong, L. L., Hanikel, N., Yaghi, O., Grun, C. N., Strauss, M. T., Bron, P., Lai‐Kee‐Him, J., Schueder, F., Wang, B., Wang, P., et al. (2017) · Nature · doi:10.1038/nature24648 · Cited by 406 · see citing works
Self-citationMoore, C., & Mertens, S. (2011) · doi:10.1093/acprof:oso/9780199233212.001.0001 · Cited by 342 · see citing works
An information-bearing seed for nucleating algorithmic self-assembly
Barish, R. D., Schulman, R., Rothemund, P. W. K., & Winfree, E. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808736106 · Cited by 267 · see citing works
Self-citationComplexity of Self‐Assembled Shapes
Soloveichik, D., & Winfree, E. (2007) · SIAM Journal on Computing · doi:10.1137/s0097539704446712 · Cited by 252 · see citing works
Self-citationThe program-size complexity of self-assembled squares
Rothemund, P. W. K., & Winfree, E. (2000) · Cited by 220 · see citing works
Self-citationProofreading Tile Sets: Error Correction for Algorithmic Self-Assembly
Winfree, E., & Bekbolatov, R. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24628-2_13 · Cited by 209 · see citing works
Self-citationSynthesis of crystals with a programmable kinetic barrier to nucleation
Schulman, R., & Winfree, E. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0701467104 · Cited by 178 · see citing works
Self-citationSimulations of Computing by Self-Assembly
Winfree, E. (1998) · CaltechAUTHORS (California Institute of Technology) · doi:10.7907/z9tb14x7 · Cited by 147 · see citing works
Self-citationTheory of algorithmic self-assembly
Doty, D. S. (2012) · Communications of the ACM · doi:10.1145/2380656.2380675 · Cited by 140 · see citing works
Self-citationRobust self-replication of combinatorial information via crystal growth and scission
Schulman, R., Yurke, B., & Winfree, E. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117813109 · Cited by 132 · see citing works
Self-citationRational design of self-assembly pathways for complex multicomponent structures
Jacobs, W. M., Reinhardt, A., & Frenkel, D. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1502210112 · Cited by 129 · see citing works
P-completeness of Cellular Automaton Rule 110
Neary, T., & Woods, D. (2006) · Lecture notes in computer science · doi:10.1007/11786986_13 · Cited by 125 · see citing works
Self-citationDirecting Self-Assembly of DNA Nanotubes Using Programmable Seeds
Mohammed, A. M., & Schulman, R. (2013) · Nano Letters · doi:10.1021/nl400881w · Cited by 99 · see citing works
Physical principles for DNA tile self-assembly
Evans, C. G., & Winfree, E. (2017) · Chemical Society Reviews · doi:10.1039/c6cs00745g · Cited by 98 · see citing works
Self-citationProgrammable Control of Nucleation for Algorithmic Self-Assembly
Schulman, R., & Winfree, E. (2009) · SIAM Journal on Computing · doi:10.1137/070680266 · Cited by 81 · see citing works
Self-citationCrystals that Count! Physical Principles and Experimental Investigations of DNA Tile Self-Assembly
Evans, C. G. (2014) · doi:10.7907/7fmk-9403 · Cited by 40 · see citing works
Growth of equilibrium structures built from a large number of distinct component types
Hedges, L. O., Mannige, R. V., & Whitelam, S. (2014) · Soft Matter · doi:10.1039/c4sm01021c · Cited by 37 · see citing works
Self-assembly of fully addressable DNA nanostructures from double crossover tiles
Wang, W., Lin, T., Zhang, S., Bai, T., Mi, Y., & Wei, B. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw670 · Cited by 34 · see citing works
Complex Reconfiguration of DNA Nanostructures
Wei, B., Ong, L. L., Chen, J. W., Jaffe, A. S., & Yin, P. (2014) · Angewandte Chemie International Edition · doi:10.1002/anie.201402437 · Cited by 32 · see citing works
Self-citationDNA Sticky End Design and Assignment for Robust Algorithmic Self-assembly
Evans, C. G., & Winfree, E. (2013) · Lecture notes in computer science · doi:10.1007/978-3-319-01928-4_5 · Cited by 19 · see citing works
Self-citationIncreasing Redundancy Exponentially Reduces Error Rates during Algorithmic Self-Assembly
Schulman, R., Wright, C., & Winfree, E. (2015) · ACS Nano · doi:10.1021/nn507493s · Cited by 16 · see citing works
Self-citationComplex Reconfiguration of DNA Nanostructures
Wei, B., Ong, L. L., Chen, J. W., Jaffe, A. S., & Yin, P. (2014) · Angewandte Chemie · doi:10.1002/ange.201402437 · Cited by 15 · see citing works
Self-citationConcentration independent random number generation in tile self-assembly
Chalk, C., Fu, B., Martinez, E., Schweller, R., & Wylie, T. (2016) · Theoretical Computer Science · doi:10.1016/j.tcs.2016.12.021 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- [8]Barish, R. D., Schulman, R., Rothemund, P. W. K. & Winfree, E. An informationbearing seed for nucleating algorithmic self-assembly. Proc. Natl Acad. Sci. USA 106 , 6054-6059 (2009).
- [18]Rothemund, P. W. K. & Winfree, E. The program-size complexity of selfassembled squares. In STOC: Proceedings of the 32nd Annual ACM Symposium on Theory of Computing (eds Yao, F. & Luks, E.) 459-468 (Association for Computing Machinery, 2000).
Cited by
Sorted by citations
Dey, S., Fan, C., Gothelf, K. V., Li, J., Lin, C., Liu, L., Liu, N., Nijenhuis, M. A. D., Saccà, B., Simmel, F. C., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-020-00009-8 · Cited by 745 · see citing works
Colloidal Self-Assembly Approaches to Smart Nanostructured Materials
Li, Z., Fan, Q., & Yin, Y. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00482 · Cited by 472 · see citing works
Functionalizing Framework Nucleic‐Acid‐Based Nanostructures for Biomedical Application
Zhang, T., Tian, T., & Lin, Y. (2021) · Advanced Materials · doi:10.1002/adma.202107820 · Cited by 372 · see citing works
Recent Advances in DNA Origami-Engineered Nanomaterials and Applications
Zhan, P., Peil, A., Jiang, Q., Wang, D., Mousavi, S., Xiong, Q., Shen, Q., Shang, Y., Ding, B., Lin, C., et al. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00028 · Cited by 362 · see citing works
Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap
Walther, A. (2019) · Advanced Materials · doi:10.1002/adma.201905111 · Cited by 336 · see citing works
Physical intelligence as a new paradigm
Sitti, M. (2021) · Extreme Mechanics Letters · doi:10.1016/j.eml.2021.101340 · Cited by 316 · see citing works
Emerging Approaches to DNA Data Storage: Challenges and Prospects
Doricchi, A., Platnich, C. M., Gimpel, A., Horn, F., Earle, M., Lanzavecchia, G., Cortajarena, A. L., Liz-Marzán, L. M., Liu, N., Heckel, R., et al. (2022) · ACS Nano · doi:10.1021/acsnano.2c06748 · Cited by 235 · see citing works
DNA-based programmable gate arrays for general-purpose DNA computing
Lv, H., Xie, N., Li, M., Dong, M., Sun, C., Zhang, Q., Zhao, L., Li, J., Zuo, X., Chen, H., et al. (2023) · Nature · doi:10.1038/s41586-023-06484-9 · Cited by 214 · see citing works
Dynamic DNA nanotechnology: toward functional nanoscale devices
DeLuca, M., Shi, Z., Castro, C. E., & Arya, G. (2019) · Nanoscale Horizons · doi:10.1039/c9nh00529c · Cited by 211 · see citing works
Engineering lattice metamaterials for extreme property, programmability, and multifunctionality
Jia, Z., Liu, F., Jiang, X., & Wang, L. (2020) · Journal of Applied Physics · doi:10.1063/5.0004724 · Cited by 169 · see citing works
Prospects and challenges of dynamic DNA nanostructures in biomedical applications
Tian, T., Li, Y., & Lin, Y. (2022) · Bone Research · doi:10.1038/s41413-022-00212-1 · Cited by 171 · see citing works
Fan, D., Wang, J., Wang, E., & Dong, S. (2020) · Advanced Science · doi:10.1002/advs.202001766 · Cited by 141 · see citing works
Programmable protein circuit design
Chen, Z., & Elowitz, M. B. (2021) · Cell · doi:10.1016/j.cell.2021.03.007 · Cited by 137 · see citing works
DNA as a universal chemical substrate for computing and data storage
Yang, S., Bögels, B. W. A., Wang, F., Xu, C., Dou, H., Mann, S., Fan, C., & de Greef, T. F. A. (2024) · Nature Reviews Chemistry · doi:10.1038/s41570-024-00576-4 · Cited by 142 · see citing works
Nonlinear decision-making with enzymatic neural networks
Okumura, S., Gines, G., Lobato‐Dauzier, N., Baccouche, A., Deteix, R., Fujii, T., Rondelez, Y., & Genot, A. J. (2022) · Nature · doi:10.1038/s41586-022-05218-7 · Cited by 116 · see citing works
Multi-micron crisscross structures grown from DNA-origami slats
Wintersinger, C. M., Minev, D., Ershova, A., Sasaki, H. M., Gowri, G., Berengut, J. F., Corea-Dilbert, F. E., Yin, P., & Shih, W. M. (2022) · Nature Nanotechnology · doi:10.1038/s41565-022-01283-1 · Cited by 106 · see citing works
Self-citationPattern recognition in the nucleation kinetics of non-equilibrium self-assembly
Evans, C. G., O’Brien, J., Winfree, E., & Murugan, A. (2024) · Nature · doi:10.1038/s41586-023-06890-z · Cited by 88 · see citing works
Self-citationLiu, Y., Li, X., Zhang, Y., Ge, L., Guan, Y., & Zhang, Z. (2023) · Small · doi:10.1002/smll.202303838 · Cited by 80 · see citing works
Liang, X., Li, L., Tang, J., Komiyama, M., & Ariga, K. (2020) · Bulletin of the Chemical Society of Japan · doi:10.1246/bcsj.20200012 · Cited by 79 · see citing works
Kim, J., Ashwanikumar, N., Patel, S., & Sahay, G. (2019) · Theranostics · doi:10.7150/thno.33921 · Cited by 78 · see citing works
An Intelligent DNA Nanorobot for Autonomous Anticoagulation
Yang, L., Zhao, Y., Xu, X., Xu, K., Zhang, M., Huang, K., Kang, H., Lin, H.-C., Yang, Y., & Han, D. (2020) · Angewandte Chemie International Edition · doi:10.1002/anie.202007962 · Cited by 77 · see citing works
Digital Sensing and Molecular Computation by an Enzyme-Free DNA Circuit
Arter, W. E., Yusim, Y., Peter, Q. A. E., Taylor, C. G., Klenerman, D., Keyser, U. F., & Knowles, T. P. J. (2020) · ACS Nano · doi:10.1021/acsnano.0c00628 · Cited by 75 · see citing works
Sengar, A., Ouldridge, T., Henrich, O., Rovigatti, L., & Šulc, P. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.693710 · Cited by 70 · see citing works
Universality of dissipative self-assembly from quantum dots to human cells
Makey, G., Galioğlu, S., Ghaffari, R., Engin, E. D., Yıldırım, G., Yavuz, Ö., Bektaş, O., Nizam, Ü. S., Akbulut, Ö., Şahin, Ö., et al. (2020) · Nature Physics · doi:10.1038/s41567-020-0879-8 · Cited by 71 · see citing works
DNA‐Based Adaptive Plasmonic Logic Gates
Dong, J., Wang, M., Zhou, Y., Zhou, C., & Wang, Q. (2020) · Angewandte Chemie International Edition · doi:10.1002/anie.202006029 · Cited by 64 · see citing works
Seeman, N. C. (2020) · Nano Letters · doi:10.1021/acs.nanolett.0c00325 · Cited by 62 · see citing works
From Molecular Electronics to Molecular Intelligence
Yan, C., Fang, C., Gan, J., Wang, J., Zhao, X. Z., Wang, X., Li, J., Zhang, Y., Liu, H., Li, X., et al. (2024) · ACS Nano · doi:10.1021/acsnano.4c10389 · Cited by 60 · see citing works
Liu, L., Hu, Q., Zhang, W., Li, W., Zhang, W., Ming, Z., Li, L., Chen, N., Wang, H., & Xiao, X. (2021) · ACS Nano · doi:10.1021/acsnano.1c01763 · Cited by 58 · see citing works
Biocomputing Based on DNA Strand Displacement Reactions
Lv, H., Li, Q., Shi, J., Fan, C., & Wang, F. (2021) · ChemPhysChem · doi:10.1002/cphc.202100140 · Cited by 57 · see citing works
Dai, Y., Xu, W. L., Somoza, R. A., Welter, J. F., Caplan, A. I., & Liu, C.-C. (2020) · Angewandte Chemie International Edition · doi:10.1002/anie.202010648 · Cited by 54 · see citing works
Electrochemical sensing based on DNA nanotechnology
Kogikoski, S., Paschoalino, W. J., Cantelli, L., da Silva, W. L., & Kubota, L. T. (2019) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2019.06.021 · Cited by 54 · see citing works
Chemical reservoir computation in a self-organizing reaction network
Baltussen, M. G., de Jong, T. J., Duez, Q., Robinson, W. E., & Huck, W. T. S. (2024) · Nature · doi:10.1038/s41586-024-07567-x · Cited by 62 · see citing works
Is stochastic thermodynamics the key to understanding the energy costs of computation?
Wolpert, D. H., Korbel, J., Lynn, C. W., Tasnim, F., Grochow, J. A., Kardeş, G., Aimone, J. B., Balasubramanian, V., DeGiuli, E., Doty, D. S., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2321112121 · Cited by 53 · see citing works
Self-citationSengar, A., Ouldridge, T. E., Henrich, O., Rovigatti, L., & Šulc, P. (2021) · Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) · Cited by 49 · see citing works
Information processing based on DNA toehold-mediated strand displacement (TMSD) reaction
Luo, T., Fan, S., Liu, Y., & Song, J. (2021) · Nanoscale · doi:10.1039/d0nr07865d · Cited by 49 · see citing works
Three-dimensional nanolithography guided by DNA modular epitaxy
Shen, J., Sun, W., Liu, D., Schaus, T. E., & Yin, P. (2021) · Nature Materials · doi:10.1038/s41563-021-00930-7 · Cited by 49 · see citing works
Self-citationChakraborty, A., Ravi, S. P., Shamiya, Y., Cui, C., & Paul, A. (2021) · Chemical Society Reviews · doi:10.1039/d0cs01387k · Cited by 48 · see citing works
Robust nucleation control via crisscross polymerization of highly coordinated DNA slats
Minev, D., Wintersinger, C. M., Ershova, A., & Shih, W. M. (2021) · Nature Communications · doi:10.1038/s41467-021-21755-7 · Cited by 48 · see citing works
Liu, J., Zhang, T., Liu, X., Lam, J. W. Y., Tang, B. Z., & Chau, Y. (2022) · Materials Horizons · doi:10.1039/d2mh00537a · Cited by 44 · see citing works
Programming DNA Self-Assembly by Geometry
Zhang, C., Zheng, M., Ohayon, Y. P., Vecchioni, S., Sha, R., Seeman, N. C., Jonoska, N., & Mao, C. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.2c02456 · Cited by 44 · see citing works
An RNA-Based Theory of Natural Universal Computation.
Akhlaghpour, H. (2020) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2021.110984 · Cited by 28 · see citing works
Modeling somatic computation with non-neural bioelectric networks
Manicka, S., & Levin, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-54859-8 · Cited by 41 · see citing works
Scalable One-Pot-Liquid-Phase Oligonucleotide Synthesis for Model Network Hydrogels
Creusen, G., Akintayo, C. O., Schumann, K., & Walther, A. (2020) · Journal of the American Chemical Society · doi:10.1021/jacs.0c05488 · Cited by 41 · see citing works
DNA-based biocomputing circuits and their biomedical applications
Jia, S., Lv, H., Li, Q., Fan, C., & Wang, F. (2025) · Nature Reviews Bioengineering · doi:10.1038/s44222-025-00303-8 · Cited by 40 · see citing works
Molecular Motor‐Driven Light‐Controlled Logic‐Gated K+ Channel for Cancer Cell Apoptosis
Li, C., Wu, Y., Zhu, Y., Yan, J., Liu, S., Xu, J., Fa, S., Yan, T., Zhu, D., Yan, Y., et al. (2024) · Advanced Materials · doi:10.1002/adma.202312352 · Cited by 39 · see citing works
Barrat, J., Gado, E. D., Egelhaaf, S. U., Mao, X., Dijkstra, M., Pine, D. J., Kumar, S. K., Bishop, K. J. M., Gang, O., Obermeyer, A. C., et al. (2023) · Journal of Physics Materials · doi:10.1088/2515-7639/ad06cc · Cited by 38 · see citing works
Cabello-García, J., Bae, W., Stan, G.-B. V., & Ouldridge, T. E. (2021) · ACS Nano · doi:10.1021/acsnano.0c10068 · Cited by 37 · see citing works
DNA dynamics and computation based on toehold-free strand displacement
Kang, H., Lin, T., Xu, X., Jia, Q., Lakerveld, R., & Wei, B. (2021) · Nature Communications · doi:10.1038/s41467-021-25270-7 · Cited by 38 · see citing works
Experimental evolution of evolvability
Barnett, M., Meister, L., & Rainey, P. B. (2025) · Science · doi:10.1126/science.adr2756 · Cited by 36 · see citing works
Amphiphilic DNA nanostructures for bottom-up synthetic biology
Rubio‐Sánchez, R., Fabrini, G., Cicuta, P., & Michele, L. D. (2021) · Chemical Communications · doi:10.1039/d1cc04311k · Cited by 36 · see citing works
Folding Double‐Stranded DNA into Designed Shapes with Triplex‐Forming Oligonucleotides
Ng, C., Samanta, A., Mandrup, O. A., Tsang, E., Youssef, S., Klausen, L. H., Dong, M., Nijenhuis, M. A. D., & Gothelf, K. V. (2023) · Advanced Materials · doi:10.1002/adma.202302497 · Cited by 36 · see citing works
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Kieffer, C., Genot, A. J., Rondelez, Y., & Gines, G. (2023) · Advanced Biology · doi:10.1002/adbi.202200203 · Cited by 35 · see citing works
Toward three-dimensional DNA industrial nanorobots
Zhou, F., Ni, H., Zhu, G., Bershadsky, L., Sha, R., Seeman, N., & Chaikin, P. M. (2023) · Science Robotics · doi:10.1126/scirobotics.adf1274 · Cited by 28 · see citing works
Self-citationHuang, P. S., Chen, M., Chen, K., Ye, S., & Yu, L. (2022) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2022.104485 · Cited by 33 · see citing works
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Emanuelson, C., Bardhan, A., & Deiters, A. (2021) · ACS Synthetic Biology · doi:10.1021/acssynbio.1c00062 · Cited by 33 · see citing works
Locked nucleic acids based DNA circuits with ultra-low leakage
Hu, H., Liu, L., Zhang, L., Zhang, W., Dong, K., Yan, B., Mu, Y., Shi, M., Li, L., & Xiao, X. (2022) · Nano Research · doi:10.1007/s12274-022-4761-0 · Cited by 31 · see citing works
Mao, D., Tang, X., Zhang, R., Chen, T., Liu, C., Gou, H., Sun, P., Mao, Y., Deng, J., Li, W., et al. (2024) · Journal of the American Chemical Society · doi:10.1021/jacs.4c00811 · Cited by 30 · see citing works
Modular reconfiguration of DNA origami assemblies using tile displacement
Sarraf, N., Rodriguez, K. R., & Qian, L. (2023) · Science Robotics · doi:10.1126/scirobotics.adf1511 · Cited by 30 · see citing works
Polydopamine-coated i-motif DNA/Gold nanoplatforms for synergistic photothermal-chemotherapy
Chen, B., Lan, M., Fan, R., Chuan, D., Ren, Y., Mu, M., Chen, H., Zou, B., & Guo, G. F. (2023) · Asian Journal of Pharmaceutical Sciences · doi:10.1016/j.ajps.2023.100781 · Cited by 29 · see citing works
Supramolecular chemistry for optical detection and delivery applications in living plants
Balli, M. V., Biedermann, F., Prodi, L., & Picchetti, P. (2025) · Chemical Society Reviews · doi:10.1039/d4cs00500g · Cited by 29 · see citing works
Single-Molecule Resettable DNA Computing via Magnetic Tweezers
Pei, Y., Bian, T., Liu, Y., Liu, Y., Xie, Y., & Song, J. (2022) · Nano Letters · doi:10.1021/acs.nanolett.2c00183 · Cited by 29 · see citing works
Wang, N., Yu, C., Xu, T., Yao, D., Zhu, L., Shen, Z., & Huang, X. (2022) · Journal of Nanobiotechnology · doi:10.1186/s12951-022-01701-5 · Cited by 29 · see citing works
Advanced unconventional techniques for sub‐100 nm nanopatterning
Guo, M., Qu, Z., Min, F., Li, Z., Qiao, Y., & Song, Y. (2022) · InfoMat · doi:10.1002/inf2.12323 · Cited by 30 · see citing works
Programming the Nucleation of DNA Brick Self‐Assembly with a Seeding Strand
Zhang, Y., Reinhardt, A., Wang, P., Song, J., & Ke, Y. (2020) · Angewandte Chemie International Edition · doi:10.1002/anie.201915063 · Cited by 26 · see citing works
Catalytic-assembly of programmable atom equivalents
Yao, D., Zhang, Y., Zhou, X., Sun, X., Liu, X., Zhou, J., Jiang, W. J., Hua, W., & Liang, H. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2219034120 · Cited by 25 · see citing works
DNA Nanotechnology-based Biocomputing
Yin, J., Wang, J., Niu, R., Ren, S., Wang, D., & Chao, J. (2020) · Chemical Research in Chinese Universities · doi:10.1007/s40242-020-9086-5 · Cited by 25 · see citing works
Empowering DNA-Based Information Processing: Computation and Data Storage
Li, K., Chen, H., Li, D., Yang, C. J., Zhang, H., & Zhu, Z. (2024) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.4c13948 · Cited by 25 · see citing works
Assembly of Complex Colloidal Systems Using DNA
Jacobs, W. M., & Rogers, W. B. (2025) · Annual Review of Condensed Matter Physics · doi:10.1146/annurev-conmatphys-032922-113138 · Cited by 24 · see citing works
Chang, W.-L., Chen, J.-C., Chung, W., Hsiao, C.-Y., Wong, R., & Vasilakos, A. V. (2021) · IEEE Transactions on NanoBioscience · doi:10.1109/tnb.2021.3075733 · Cited by 24 · see citing works
Abdollahzadeh, H., Peeples, T. L., & Shahcheraghi, M. (2025) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2025.115673 · Cited by 24 · see citing works
Groeer, S., Schumann, K., Loescher, S., & Walther, A. (2021) · Science Advances · doi:10.1126/sciadv.abj5827 · Cited by 23 · see citing works
Regulation of 2D DNA Nanostructures by the Coupling of Intrinsic Tile Curvature and Arm Twist
Jiang, C., Lu, B., Zhang, W., Ohayon, Y. P., Feng, F., Li, S., Seeman, N. C., & Xiao, S. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.1c13601 · Cited by 23 · see citing works
Network topology–directed design of molecular CPU for cell-like dynamic information processing
Wang, D., Yang, Y., Chen, F., Lyu, Y., & Tan, W. (2022) · Science Advances · doi:10.1126/sciadv.abq0917 · Cited by 23 · see citing works
Creusen, G., Schmidt, R. S., & Walther, A. (2021) · ACS Macro Letters · doi:10.1021/acsmacrolett.1c00211 · Cited by 23 · see citing works
Fan, D., Wang, J., Han, J., Wang, E., & Dong, S. (2021) · Science China Chemistry · doi:10.1007/s11426-021-1131-1 · Cited by 22 · see citing works
Programmable polymer materials empowered by DNA nanotechnology
Speed, S. K., Gupta, K., Peng, Y., Hsiao, S., & Krieg, E. (2023) · Journal of Polymer Science · doi:10.1002/pol.20230160 · Cited by 22 · see citing works
Minds, Machines, and Molecules
Brunet, T. D. P., & Halina, M. (2020) · Philosophical Topics · doi:10.5840/philtopics202048111 · Cited by 21 · see citing works
pH-Controlled Resettable Modular DNA Strand-Displacement Circuits
Sun, X., Yao, D., & Liang, H. (2023) · Nano Letters · doi:10.1021/acs.nanolett.3c03265 · Cited by 21 · see citing works
Chen, Y., Sun, W., Yang, C. J., & Zhu, Z. (2020) · ACS Applied Bio Materials · doi:10.1021/acsabm.0c00035 · Cited by 21 · see citing works
Wei, J., Xing, J., Hou, X., Chen, X., & Li, Q. (2024) · Advanced Materials · doi:10.1002/adma.202411291 · Cited by 20 · see citing works
Repeated Reuse of Deoxyribozyme-Based Logic Gates
Harding, B. I., Pollak, N. M., Stefanović, D., & Macdonald, J. (2019) · Nano Letters · doi:10.1021/acs.nanolett.9b02326 · Cited by 20 · see citing works
DNA Balance for Native Characterization of Chemically Modified DNA
Wang, G. A., Xu, J., Traynor, S. M., Chen, H.-D., Eljabu, F. M., Wu, X., Yan, H., & Li, F. (2021) · Journal of the American Chemical Society · doi:10.1021/jacs.1c05236 · Cited by 20 · see citing works
Plasmonic metasurfaces: Light-matter interactions, fabrication, applications and future outlooks
Yang, F., Cao, W., Zheng, G., Qiu, L., Nie, Z., & Li, Y. (2025) · Progress in Materials Science · doi:10.1016/j.pmatsci.2025.101508 · Cited by 19 · see citing works
DNA strand displacement based computational systems and their applications
Chen, C., Wen, J., Wen, Z.-B., Song, S., & Shi, X. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1120791 · Cited by 19 · see citing works
Advanced Biomimetic and Biohybrid Magnetic Micro/Nano‐Machines
Murali, N., Das, S. B., Yadav, S., Rainu, S. K., Singh, N., & Betal, S. (2024) · Advanced Materials Technologies · doi:10.1002/admt.202400239 · Cited by 19 · see citing works
Liao, Y., Hu, H., Tang, X., Qin, Y., Zhang, W., Dong, K., Yan, B., Mu, Y., Li, L., Ming, Z., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1193 · Cited by 16 · see citing works
Dore, M. D., Rafique, M. G., Yang, T. P., Zorman, M. L., Platnich, C. M., Xu, P., Trinh, T., Rizzuto, F. J., Cosa, G., Li, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48722-2 · Cited by 17 · see citing works
Kinetic Proofreading Can Enhance Specificity in a Nonenzymatic DNA Strand Displacement Network
Mukherjee, R., Sengar, A., Cabello-García, J., & Ouldridge, T. E. (2024) · Journal of the American Chemical Society · doi:10.1021/jacs.3c14673 · Cited by 17 · see citing works
Energy Landscapes and Hybridization Pathways for DNA Hexamer Duplexes
Xiao, S., Sharpe, D., Chakraborty, D., & Wales, D. J. (2019) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.9b02356 · Cited by 17 · see citing works
Feedback regulation of crystal growth by buffering monomer concentration
Schaffter, S. W., Scalise, D., Murphy, T. M., Patel, A., & Schulman, R. (2020) · Nature Communications · doi:10.1038/s41467-020-19882-8 · Cited by 17 · see citing works
Logic devices based on nucleic acid self‐assembly
Xu, X., Shang, Y., Liu, F., Jiang, Q., & Ding, B. (2021) · InfoMat · doi:10.1002/inf2.12240 · Cited by 17 · see citing works
Evaluating the effects of hydrophobic and cationic residues on antimicrobial peptide self-assembly
Cao, F., Ma, G., Song, M., Zhu, G., Mei, L., & Qin, Q. (2021) · Soft Matter · doi:10.1039/d1sm00096a · Cited by 17 · see citing works
Developmental Self-Assembly of a DNA Ring with Stimulus-Responsive Size and Growth Direction
Glynn, A. T., Davidson, S. R., & Qian, L. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.2c03853 · Cited by 16 · see citing works
Accelerating the characterization of dynamic DNA origami devices with deep neural networks
Wang, Y., Jin, X., & Castro, C. (2023) · Scientific Reports · doi:10.1038/s41598-023-41459-w · Cited by 16 · see citing works
Heterometallic macromolecules: Synthesis, properties and multiple nanomaterial applications
Liu, F., Liu, X., Abdiryim, T., Gu, H., & Astruc, D. (2023) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2023.215544 · Cited by 16 · see citing works
Reconfigurable nanomaterials folded from multicomponent chains of DNA origami voxels
Luu, M. T., Berengut, J. F., Li, J., Chen, J.-B., Singh, J. K. D., Glieze, K. C. D., Turner, M., Skipper, K., Meppat, S., Fowler, H., et al. (2024) · Science Robotics · doi:10.1126/scirobotics.adp2309 · Cited by 16 · see citing works
Tunable and Large-Scale Model Network StarPEG-DNA Hydrogels
Akintayo, C. O., Creusen, G., Straub, P., & Walther, A. (2021) · Macromolecules · doi:10.1021/acs.macromol.1c00600 · Cited by 16 · see citing works
An Intelligent DNA Nanorobot for Autonomous Anticoagulation
Yang, L., Zhao, Y., Xu, X., Xu, K., Zhang, M., Huang, K., Kang, H., Lin, H.-C., Yang, Y., & Han, D. (2020) · Angewandte Chemie · doi:10.1002/ange.202007962 · Cited by 16 · see citing works
Towards a Passive Self-Assembling Macroscale Multi-Robot System
Jílek, M., Somr, M., Kulich, M., Zeman, J., & Přeučil, L. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3096748 · Cited by 16 · see citing works
scadnano: A Browser-Based, Scriptable Tool for Designing DNA NanostructuresPreprint
Doty, D. S., Lee, B. L., & Stérin, T. (2020) · arXiv (Cornell University) · doi:10.4230/lipics.dna.2020.9 · Cited by 16 · see citing works
Self-citation
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › 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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