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    Research Article

    Automated Selection of Synthetic Biology Parts for Genetic Regulatory Networks
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    † Raytheon BBN Technologies, 10 Moulton St., Cambridge, Massachusetts, United States
    ‡ § Departments of ‡Electrical and Computer Engineering and §Bioinformatics, Boston University, Boston, Massachusetts, United States
    *E-mail: [email protected]
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    ACS Synthetic Biology

    Cite this: ACS Synth. Biol. 2012, 1, 8, 332–344
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    https://doi.org/10.1021/sb300032y
    Published July 6, 2012
    Copyright © 2012 American Chemical Society
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    Abstract

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    Raising the level of abstraction for synthetic biology design requires solving several challenging problems, including mapping abstract designs to DNA sequences. In this paper we present the first formalism and algorithms to address this problem. The key steps of this transformation are feature matching, signal matching, and part matching. Feature matching ensures that the mapping satisfies the regulatory relationships in the abstract design. Signal matching ensures that the expression levels of functional units are compatible. Finally, part matching finds a DNA part sequence that can implement the design. Our software tool MatchMaker implements these three steps.

    Copyright © 2012 American Chemical Society

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    Supporting Information

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    (1) Detailed complexity discussion including the proof of the feature matching problem and (2) sample feature and signal Clotho databases used with MatchMaker as an SQL file (MatchMaker.sql). This material is available free of charge via the Internet at http://pubs.acs.org.

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    Cited By

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    ACS Synthetic Biology

    Cite this: ACS Synth. Biol. 2012, 1, 8, 332–344
    Click to copy citationCitation copied!
    https://doi.org/10.1021/sb300032y
    Published July 6, 2012
    Copyright © 2012 American Chemical Society
    Request reuse permissions

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