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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. DNA 2017. Lecture Notes in Computer Science (10467). Springer, Cham, Switzerland, pp. 249-266. ISBN 978-3-319-66799-7

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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
    Additional Information: This paper was presented at the 23rd International Conference, DNA 23, Austin, TX, USA, September 24–28, 2017.
    Keywords: DNA; Nanostructures; Origami nanostructures; Binding sites; Bins; Boolean algebra; Calculations; Physical chemistry; Assembly systems; Binary counters; Chemical systems; DNA nanotechnology; Molecular computing; Self-assembling; Thermodynamic driving forces; Thermodynamic equilibria; Thermodynamics;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 12072
    Identification Number: https://doi.org/10.1007/978-3-319-66799-7_16
    Depositing User: Trent Rogers
    Date Deposited: 02 Jan 2020 13:08
    Publisher: Springer
    Refereed: Yes
    URI:

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