Recombinase-based genetic circuit optimization

Chun Ning Lai; Jie Hong R. Jiang; Francois Fages

doi:10.1109/BIOCAS.2017.8325220

Recombinase-based genetic circuit optimization

Chun Ning Lai, Jie Hong R. Jiang, Francois Fages

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The rapid advancements of synthetic biology show promising potential in biomedical and other applications. Recently, recombinases were proposed as a tool to engineer genetic logic circuits with long-term memory in living and even mammalian cells. The technology is under active development, and the complexity of engineered genetic circuits grows continuously. However, how to minimize a genetic circuit composed of recombinase-based logic gates remain largely open. In this paper, we formulate the problem as a cubic-time assignment problem and solved by a 0/1-ILP solver to minimize DNA sequence length of genetic circuits. Experimental results show effective reduction of our optimization method, which may be crucial to enable practical realization of complex genetic circuits.

Original language	English
Title of host publication	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781509058037
DOIs	https://doi.org/10.1109/BIOCAS.2017.8325220
Publication status	Published - 2 Jul 2017
Externally published	Yes
Event	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Torino, Italy Duration: 19 Oct 2017 → 21 Oct 2017

Publication series

Name	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
Volume	2018-January

Conference

Conference	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017
Country/Territory	Italy
City	Torino
Period	19/10/17 → 21/10/17

Access to Document

10.1109/BIOCAS.2017.8325220

Cite this

Lai, C. N., Jiang, J. H. R., & Fages, F. (2017). Recombinase-based genetic circuit optimization. In 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings (pp. 1-4). (2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIOCAS.2017.8325220

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title = "Recombinase-based genetic circuit optimization",

abstract = "The rapid advancements of synthetic biology show promising potential in biomedical and other applications. Recently, recombinases were proposed as a tool to engineer genetic logic circuits with long-term memory in living and even mammalian cells. The technology is under active development, and the complexity of engineered genetic circuits grows continuously. However, how to minimize a genetic circuit composed of recombinase-based logic gates remain largely open. In this paper, we formulate the problem as a cubic-time assignment problem and solved by a 0/1-ILP solver to minimize DNA sequence length of genetic circuits. Experimental results show effective reduction of our optimization method, which may be crucial to enable practical realization of complex genetic circuits.",

author = "Lai, \{Chun Ning\} and Jiang, \{Jie Hong R.\} and Francois Fages",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 ; Conference date: 19-10-2017 Through 21-10-2017",

year = "2017",

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doi = "10.1109/BIOCAS.2017.8325220",

language = "English",

series = "2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Lai, CN, Jiang, JHR & Fages, F 2017, Recombinase-based genetic circuit optimization. in 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings. 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017, Torino, Italy, 19/10/17. https://doi.org/10.1109/BIOCAS.2017.8325220

Recombinase-based genetic circuit optimization. / Lai, Chun Ning; Jiang, Jie Hong R.; Fages, Francois.
2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-4 (2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The rapid advancements of synthetic biology show promising potential in biomedical and other applications. Recently, recombinases were proposed as a tool to engineer genetic logic circuits with long-term memory in living and even mammalian cells. The technology is under active development, and the complexity of engineered genetic circuits grows continuously. However, how to minimize a genetic circuit composed of recombinase-based logic gates remain largely open. In this paper, we formulate the problem as a cubic-time assignment problem and solved by a 0/1-ILP solver to minimize DNA sequence length of genetic circuits. Experimental results show effective reduction of our optimization method, which may be crucial to enable practical realization of complex genetic circuits.

AB - The rapid advancements of synthetic biology show promising potential in biomedical and other applications. Recently, recombinases were proposed as a tool to engineer genetic logic circuits with long-term memory in living and even mammalian cells. The technology is under active development, and the complexity of engineered genetic circuits grows continuously. However, how to minimize a genetic circuit composed of recombinase-based logic gates remain largely open. In this paper, we formulate the problem as a cubic-time assignment problem and solved by a 0/1-ILP solver to minimize DNA sequence length of genetic circuits. Experimental results show effective reduction of our optimization method, which may be crucial to enable practical realization of complex genetic circuits.

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DO - 10.1109/BIOCAS.2017.8325220

M3 - Conference contribution

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T3 - 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings

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BT - 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017

Y2 - 19 October 2017 through 21 October 2017

ER -

Recombinase-based genetic circuit optimization

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