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• W260122569 startingPage "5760" @default.
• W260122569 abstract "While biology demonstrates that molecules can reliably transfer information and compute, design principles for implementing complex molecular computations in vitro are still being developed. In electronic computers, large-scale computation is made possible by redundancy, which allows errors to be detected and corrected. Increasing the amount of redundancy can exponentially reduce errors. Here, we use algorithmic self-assembly, a generalization of crystal growth in which the self-assembly process executes a program for growing an object, to examine experimentally whether redundancy can analogously reduce the rate at which errors occur during molecular self-assembly. We designed DNA double-crossover molecules to algorithmically self-assemble ribbon crystals that repeatedly copy a short bitstring, and we measured the error rate when each bit is encoded by 1 molecule, or redundantly encoded by 2, 3, or 4 molecules. Under our experimental conditions, each additional level of redundancy decreases the bitwise error rate by a factor of roughly 3, with the 4-redundant encoding yielding an error rate less than 0.1%. While theory and simulation predict that larger improvements in error rates are possible, our results already suggest that by using sufficient redundancy it may be possible to algorithmically self-assemble micrometer-sized objects with programmable, nanometer-scale features." @default.
• W260122569 created "2016-06-24" @default.
• W260122569 creator A5000956443 @default.
• W260122569 creator A5062069511 @default.
• W260122569 creator A5065339049 @default.
• W260122569 date "2015-05-12" @default.
• W260122569 modified "2023-10-15" @default.
• W260122569 title "Increasing Redundancy Exponentially Reduces Error Rates during Algorithmic Self-Assembly" @default.
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• W260122569 doi "https://doi.org/10.1021/nn507493s" @default.
• W260122569 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25965580" @default.
• W260122569 hasPublicationYear "2015" @default.
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