Journal article
Automated Selection of Synthetic Biology Parts for Genetic Regulatory Networks
ACS synthetic biology, Vol.1(8), pp.332-344
08/17/2012
DOI: 10.1021/sb300032y
PMID: 23651287
Abstract
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.
Details
- Title: Subtitle
- Automated Selection of Synthetic Biology Parts for Genetic Regulatory Networks
- Creators
- Fusun Yaman - RTXSwapnil Bhatia - Boston UniversityAaron Adler - RTXDouglas Densmore - Boston UniversityJacob Beal - RTX
- Resource Type
- Journal article
- Publication Details
- ACS synthetic biology, Vol.1(8), pp.332-344
- Publisher
- Amer Chemical Soc
- DOI
- 10.1021/sb300032y
- PMID
- 23651287
- ISSN
- 2161-5063
- eISSN
- 2161-5063
- Number of pages
- 13
- Grant note
- HR0011-10-C-0168 / DARPA; United States Department of Defense; Defense Advanced Research Projects Agency (DARPA)
- Language
- English
- Date published
- 08/17/2012
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984627248002771
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