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Optimizing Tile Set Size While Preserving Proofreading with a DNA Self-assembly Compiler

Evans, Constantine G. and Winfree, Erik (2018) Optimizing Tile Set Size While Preserving Proofreading with a DNA Self-assembly Compiler. In: DNA Computing and Molecular Programming. Lecture Notes in Computer Science. No.11145. Springer , Cham, pp. 37-54. ISBN 978-3-030-00029-5.

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Algorithmic DNA tile systems have the potential to allow the construction by self-assembly of large structures with complex nanometer-scale details out of relatively few monomer types, but are constrained by errors in growth and the limited sequence space of orthogonal DNA sticky ends that program tile interactions. We present a tile set optimization technique that, through analysis of algorithmic growth equivalence, potentially sensitive error pathways, and potential lattice defects, can significantly reduce the size of tile systems while preserving proofreading behavior that is essential for obtaining low error rates. Applied to systems implementing multiple algorithms that are far beyond the size of currently feasible implementations, the optimization technique results in systems that are comparable in size to already-implemented experimental systems.

Item Type:Book Section
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URLURL TypeDescription ReadCube access
Evans, Constantine G.0000-0002-7053-1670
Winfree, Erik0000-0002-5899-7523
Additional Information:© 2018 Springer Nature Switzerland AG. First Online: 07 September 2018. We thank Chigozie Nri, Philip Petersen, Lulu Qian, and Grigory Tikhomirov for discussions and collaboration on physical implementations and the Alhambra compiler, and Robert Johnson and William Poole for discussions on aTAM equivalence. This work was partially supported by the Evans Foundation and National Science Foundation award CCF-1317694.
Funding AgencyGrant Number
Evans FoundationUNSPECIFIED
Series Name:Lecture Notes in Computer Science
Issue or Number:11145
Record Number:CaltechAUTHORS:20200811-140005797
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104917
Deposited By: Tony Diaz
Deposited On:11 Aug 2020 21:10
Last Modified:16 Nov 2021 18:37

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