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Thermodynamic Binding Networks

Doty, David and Rogers, Trent A. and Soloveichik, David and Thachuk, Chris and Woods, Damien (2017) Thermodynamic Binding Networks. In: DNA Computing and Molecular Programming. Lecture Notes in Computer Science. No.10467. Springer , Cham, Switzerland, pp. 249-266. ISBN 978-3-319-66798-0. http://resolver.caltech.edu/CaltechAUTHORS:20181126-082746938

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Abstract

Strand displacement and tile assembly systems are designed to follow prescribed kinetic rules (i.e., exhibit a specific time-evolution). However, the expected behavior in the limit of infinite time—known as thermodynamic equilibrium—is often incompatible with the desired computation. Basic physical chemistry implicates this inconsistency as a source of unavoidable error. Can the thermodynamic equilibrium be made consistent with the desired computational pathway? In order to formally study this question, we introduce a new model of molecular computing in which computation is driven by the thermodynamic driving forces of enthalpy and entropy. To ensure greatest generality we do not assume that there are any constraints imposed by geometry and treat monomers as unstructured collections of binding sites. In this model we design Boolean AND/OR formulas, as well as a self-assembling binary counter, where the thermodynamically favored states are exactly the desired final output configurations. Though inspired by DNA nanotechnology, the model is sufficiently general to apply to a wide variety of chemical systems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-3-319-66799-7_16DOIArticle
Additional Information:© Springer International Publishing AG 2017. First Online: 24 August 2017. D. Doty—Supported by NSF grant CCF-1619343. T.A. Rogers—Supported by the NSF Graduate Research Fellowship Program under Grant No. DGE-1450079, NSF Grant CAREER-1553166, and NSF Grant CCF-1422152. D. Soloveichik—Supported by NSF grants CCF-1618895 and CCF-1652824. C. Thachuk—Supported by NSF grant CCF-1317694. D. Woods—Part of this work was carried out at California Institute of Technology. Supported by Inria (France) as well as National Science Foundation (USA) grants CCF-1219274, CCF-1162589, CCF-1317694.
Funders:
Funding AgencyGrant Number
NSFCCF-1619343
NSF Graduate Research FellowshipDGE-1450079
NSFCCF-1553166
NSFCCF-1422152
NSFCCF-1618895
NSFCCF-1652824
NSFCCF-1317694
Institut national de recherche en informatique et en automatique (INRIA)UNSPECIFIED
NSFCCF-1219274
NSFCCF-1162589
Record Number:CaltechAUTHORS:20181126-082746938
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181126-082746938
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:91148
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:26 Nov 2018 17:44
Last Modified:26 Nov 2018 17:44

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