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Addressing biological uncertainties in engineering gene circuits.
Zhang, Carolyn; Tsoi, Ryan; You, Lingchong.
Afiliación
  • Zhang C; Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, USA.
Integr Biol (Camb) ; 8(4): 456-64, 2016 Apr 18.
Article en En | MEDLINE | ID: mdl-26674800
ABSTRACT
Synthetic biology has grown tremendously over the past fifteen years. It represents a new strategy to develop biological understanding and holds great promise for diverse practical applications. Engineering of a gene circuit typically involves computational design of the circuit, selection of circuit components, and test and optimization of circuit functions. A fundamental challenge in this process is the predictable control of circuit function due to multiple layers of biological uncertainties. These uncertainties can arise from different sources. We categorize these uncertainties into incomplete quantification of parts, interactions between heterologous components and the host, or stochastic dynamics of chemical reactions and outline potential design strategies to minimize or exploit them.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ingeniería Genética / Biología Sintética Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Integr Biol (Camb) Asunto de la revista: BIOLOGIA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ingeniería Genética / Biología Sintética Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Integr Biol (Camb) Asunto de la revista: BIOLOGIA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos