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

Graduate Institute of Electronics Engineering
National Taiwan University
Université Paris-Saclay

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

1 Citation (Scopus)

Résumé

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.

langue originale	Anglais
titre	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
Editeur	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Nombre de pages	4
ISBN (Electronique)	9781509058037
Les DOIs	https://doi.org/10.1109/BIOCAS.2017.8325220
état	Publié - 2 juil. 2017
Modification externe	Oui
Evénement	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Torino, Italie Durée: 19 oct. 2017 → 21 oct. 2017

Série de publications

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

Une conférence

Une conférence	2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017
Pays/Territoire	Italie
La ville	Torino
période	19/10/17 → 21/10/17

Accès au document

10.1109/BIOCAS.2017.8325220

Contient cette citation

Lai, C. N., Jiang, J. H. R., & Fages, F. (2017). Recombinase-based genetic circuit optimization. Dans 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings (p. 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",

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Lai, CN, Jiang, JHR & Fages, F 2017, Recombinase-based genetic circuit optimization. Dans 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., p. 1-4, 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017, Torino, Italie, 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).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

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T1 - Recombinase-based genetic circuit optimization

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PY - 2017/7/2

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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

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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.

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Y2 - 19 October 2017 through 21 October 2017

ER -

Recombinase-based genetic circuit optimization

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Une conférence

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