Citation
Winfree, Erik (1998) Algorithmic self-assembly of DNA. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-05192003-110022
Abstract
How can molecules compute? In his early studies of reversible computation, Bennett imagined an enzymatic Turing Machine which modified a hetero-polymer (such as DNA) to perform computation with asymptotically low energy expenditures. Adleman's recent experimental demonstration of a DNA computation, using an entirely different approach, has led to a wealth of ideas for how to build DNA-based computers in the laboratory, whose energy efficiency, information density, and parallelism may have potential to surpass conventional electronic computers for some purposes. In this thesis, I examine one mechanism used in all designs for DNA-based computer -- the self-assembly of DNA by hybridization and formation of the double helix -- and show that this mechanism alone in theory can perform universal computation. To do so, I borrow an important result in the mathematical theory of tiling: Wang showed how jigsaw-shaped tiles can be designed to simulate the operation of any Turing Machine. I propose constructing molecular Wang tiles using the branched DNA constructions of Seeman, thereby producing self-assembled and algorithmically patterned two-dimensional lattices of DNA. Simulations of plausible self-assembly kinetics suggest that low error rates can be obtained near the melting temperature of the lattice; under these conditions, self-assembly is performing reversible computation with asymptotically low energy expenditures. Thus encouraged, I have begun an experimental investigation of algorithmic self-assembly. A competition experiment suggests that an individual logical step can proceed correctly by self-assembly, while a companion experiment demonstrates that unpatterned two dimensional lattices of DNA will self-assemble and can be visualized. We have reason to hope, therefore, that this experimental system will prove fruitful for investigating issues in the physics of computation by self-assembly. It may also lead to interesting new materials.
| Item Type: | Thesis (Dissertation (Ph.D.)) |
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| Degree Grantor: | California Institute of Technology |
| Division: | Engineering and Applied Science |
| Major Option: | Computation and Neural Systems |
| Thesis Availability: | Public (worldwide access) |
| Research Advisor(s): |
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| Thesis Committee: |
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| Defense Date: | 19 May 1998 |
| Author Email: | winfree (AT) caltech.edu |
| Record Number: | CaltechETD:etd-05192003-110022 |
| Persistent URL: | http://resolver.caltech.edu/CaltechETD:etd-05192003-110022 |
| Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. |
| ID Code: | 1866 |
| Collection: | CaltechTHESIS |
| Deposited By: | Imported from ETD-db |
| Deposited On: | 19 May 2003 |
| Last Modified: | 26 Dec 2012 02:43 |
Thesis Files
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PDF (winfree_thesis.pdf)
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Postscript (winfree_thesis.ps)
- Final Version
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