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Universal Computation and Optimal Construction in the Chemical Reaction Network-Controlled Tile Assembly Model

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DNA Computing and Molecular Programming (DNA 2015)

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Abstract

Tile-based self-assembly and chemical reaction networks provide two well-studied models of scalable DNA-based computation. Although tile self-assembly provides a powerful framework for describing Turing-universal self-assembling systems, assembly logic in tile self-assembly is localized, so that only the nearby environment can affect the process of self-assembly. We introduce a new model of tile-based self-assembly in which a well-mixed chemical reaction network interacts with self-assembling tiles to exert non-local control on the self-assembly process. Through simulation of multi-stack machines, we demonstrate that this new model is efficiently Turing-universal, even when restricted to unbounded space in only one spatial dimension. Using a natural notion of program complexity, we also show that this new model can produce many complex shapes with programs of lower complexity. Most notably, we show that arbitrary connected shapes can be produced by a program with complexity bounded by the Kolmogorov complexity of the shape, without the large scale factor that is required for the analogous result in the abstract tile assembly model. These results suggest that controlled self-assembly provides additional algorithmic power over tile-only self-assembly, and that non-local control enhances our ability to perform computation and algorithmically self-assemble structures from small input programs.

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Acknowledgements

We acknowledge financial support from National Science Foundation grant CCF-1317694. We also thank Dave Doty, for his helpful comments and suggestions, and Kevin Li, for his useful suggestions on an early draft of this paper.

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Correspondence to Erik Winfree .

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Schiefer, N., Winfree, E. (2015). Universal Computation and Optimal Construction in the Chemical Reaction Network-Controlled Tile Assembly Model. In: Phillips, A., Yin, P. (eds) DNA Computing and Molecular Programming. DNA 2015. Lecture Notes in Computer Science(), vol 9211. Springer, Cham. https://doi.org/10.1007/978-3-319-21999-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-21999-8_3

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