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Design of Autonomous DNA Cellular Automata
| Book Series | Lecture Notes in Computer Science |
| Publisher | Springer Berlin / Heidelberg |
| ISSN | 0302-9743 (Print) 1611-3349 (Online) |
| Volume | Volume 3892/2006 |
| Book | DNA Computing |
| DOI | 10.1007/11753681 |
| Copyright | 2006 |
| ISBN | 978-3-540-34161-1 |
| DOI | 10.1007/11753681_32 |
| Pages | 399-416 |
| Subject Collection | Computer Science |
| SpringerLink Date | Saturday, July 29, 2006 |
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Design of Autonomous DNA Cellular Automata
Peng Yin1 , Sudheer Sahu1 , Andrew J. Turberfield2 and John H. Reif1 
| (1) |
Department of Computer Science, Duke University, Box 90129, Durham, NC 27708-0129, USA |
| (2) |
University of Oxford, Department of Physics, Clarendon Laboratory, Parks Road, Oxford OX 1 3PU, UK |
Abstract
Recent experimental progress in DNA lattice construction, DNA robotics, and DNA computing provides the basis for designing
DNA cellular computing devices, i.e. autonomous nano-mechanical DNA computing devices embedded in DNA lattices. Once assembled, DNA cellular computing devices
can serve as reusable, compact computing devices that perform (universal) computation, and programmable robotics devices that
demonstrate complex motion. As a prototype of such devices, we recently reported the design of an Autonomous DNA Turing Machine,
which is capable of universal sequential computation, and universal translational motion, i.e. the motion of the head of a single tape universal mechanical Turing machine. In this paper, we describe the design of an
Autonomous DNA Cellular Automaton (ADCA), which can perform parallel universal computation by mimicking a one-dimensional (1D) universal cellular automaton. In the computation process, this
device, embedded in a 1D DNA lattice, also demonstrates well coordinated parallel motion. The key technical innovation here
is a molecular mechanism that synchronizes pipelined “molecular reaction waves” along a 1D track, and in doing so, realizes
parallel computation. We first describe the design of ADCA on an abstract level, and then present detailed DNA sequence level
implementation using commercially available protein enzymes. We also discuss how to extend the 1D design to 2D.
The work is supported by NSF ITR Grants EIA-0086015 and CCR-0326157, NSF QuBIC Grants EIA-0218376 and EIA-0218359, and DARPA/AFSOR
Contract F30602-01-2-0561.
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