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DNA Sticky End Design and Assignment for Robust Algorithmic Self-assembly

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DNA Computing and Molecular Programming (DNA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8141))

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Abstract

A major challenge in practical DNA tile self-assembly is the minimization of errors. Using the kinetic Tile Assembly Model, a theoretical model of self-assembly, it has been shown that errors can be reduced through abstract tile set design. In this paper, we instead investigate the effects of “sticky end” sequence choices in systems using the kinetic model along with the nearest-neighbor model of DNA interactions. We show that both the sticky end sequences present in a system and their positions in the system can significantly affect error rates, and propose algorithms for sequence design and assignment.

The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-01928-4_15

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Author information

Authors and Affiliations

  1. Physics, California Institute of Technology, USA

    Constantine G. Evans

  2. Computer Science, California Institute of Technology, USA

    Erik Winfree

Authors
  1. Constantine G. Evans
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  2. Erik Winfree
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Editor information

Editors and Affiliations

  1. Center for Systems and Synthetic Biology, University of California, 1700 4th Street, San Francisco, 94158, CA, USA

    David Soloveichik

  2. Materials Science and Engineering Department, Boise State University, 1910 University Drive, 83725, Boise, ID, USA

    Bernard Yurke

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Evans, C.G., Winfree, E. (2013). DNA Sticky End Design and Assignment for Robust Algorithmic Self-assembly. In: Soloveichik, D., Yurke, B. (eds) DNA Computing and Molecular Programming. DNA 2013. Lecture Notes in Computer Science, vol 8141. Springer, Cham. https://doi.org/10.1007/978-3-319-01928-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-01928-4_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01927-7

  • Online ISBN: 978-3-319-01928-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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