A coding framework for DNA self-assembly

Authors:
Zahra Mashreghian Arani;Masoud Hashempour;Fabrizio Lombardi
Affiliations:
Northeastern University, Dept. of ECE, Boston MA 02115, USA;Northeastern University, Dept. of ECE, Boston MA 02115, USA;Northeastern University, Dept. of ECE, Boston MA 02115, USA
Venue:
NANOARCH '09 Proceedings of the 2009 IEEE/ACM International Symposium on Nanoscale Architectures
Year:
2009

Citing 6
Cited 1

Error detection/correction in DNA algorithmic self-assembly

Proceedings of the conference on Design, automation and test in Europe
Checkpointing of Rectilinear Growth in DNA Self-Assembly

DFT '08 Proceedings of the 2008 IEEE International Symposium on Defect and Fault Tolerance of VLSI Systems
Complexity of compact proofreading for self-assembled patterns

DNA'05 Proceedings of the 11th international conference on DNA Computing
Error free self-assembly using error prone tiles

DNA'04 Proceedings of the 10th international conference on DNA computing
Compact error-resilient computational DNA tiling assemblies

DNA'04 Proceedings of the 10th international conference on DNA computing
Synthesis of Tile Sets for DNA Self-Assembly

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Multiple error detection in DNA self-assembly using coded tiles

IEEE Transactions on Circuits and Systems II: Express Briefs

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Abstract

This paper proposes a novel framework in which DNA self-assembly can be analyzed for error detection/location. The proposed framework relies on coding and mapping functions that allow to establish the presence of erroneous bonded tiles based on the pattern to be assembled (as defined by the tile set) and its current aggregate. As a widely used pattern and instantiation of this process, the Sierpinski Triangle self-assembly is analyzed in detail. Different properties are proposed and shown to be applicable for tile error detection/correction. Simulation results are presented to show the application of the proposed coding framework to the Sierpinski Triangle self-assembly for nano-manufacturing.