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The tile complexity of linear assemblies

Publication ,  Journal Article
Chandran, H; Gopalkrishnan, N; Reif, J
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
November 12, 2009

The conventional Tile Assembly Model (TAM) developed by Winfree using Wang tiles is a powerful, Turing-universal theoretical framework which models varied self-assembly processes. We describe a natural extension to TAM called the Probabilistic Tile Assembly Model (PTAM) to model the inherent probabilistic behavior in physically realized self-assembled systems. A particular challenge in DNA nanoscience is to form linear assemblies or rulers of a specified length using the smallest possible tile set. These rulers can then be used as components for construction of other complex structures. In TAM, a deterministic linear assembly of length N requires a tile set of cardinality at least N. In contrast, for any given N, we demonstrate linear assemblies of expected length N with a tile set of cardinality Θ(logN) and prove a matching lower bound of Ω(logN). We also propose a simple extension to PTAM called κ-pad systems in which we associate κ pads with each side of a tile, allowing abutting tiles to bind when at least one pair of corresponding pads match and prove analogous results. All our probabilistic constructions are free from co-operative tile binding errors and can be modified to produce assemblies whose probability distribution of lengths has arbitrarily small tail bounds dropping exponentially with a given multiplicative factor increase in number of tile types. Thus, for linear assembly systems, we have shown that randomization can be exploited to get large improvements in tile complexity at a small expense of precision in length. © 2009 Springer Berlin Heidelberg.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

November 12, 2009

Volume

5555 LNCS

Issue

PART 1

Start / End Page

235 / 253

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Chandran, H., Gopalkrishnan, N., & Reif, J. (2009). The tile complexity of linear assemblies. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5555 LNCS(PART 1), 235–253. https://doi.org/10.1007/978-3-642-02927-1_21
Chandran, H., N. Gopalkrishnan, and J. Reif. “The tile complexity of linear assemblies.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5555 LNCS, no. PART 1 (November 12, 2009): 235–53. https://doi.org/10.1007/978-3-642-02927-1_21.
Chandran H, Gopalkrishnan N, Reif J. The tile complexity of linear assemblies. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2009 Nov 12;5555 LNCS(PART 1):235–53.
Chandran, H., et al. “The tile complexity of linear assemblies.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5555 LNCS, no. PART 1, Nov. 2009, pp. 235–53. Scopus, doi:10.1007/978-3-642-02927-1_21.
Chandran H, Gopalkrishnan N, Reif J. The tile complexity of linear assemblies. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2009 Nov 12;5555 LNCS(PART 1):235–253.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

November 12, 2009

Volume

5555 LNCS

Issue

PART 1

Start / End Page

235 / 253

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences