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Cited by 449

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Contextualizing context for synthetic biology – identifying causes of failure of synthetic biological systems

Open access
Cardinale, Stefano, Arkin, Adam Paul·2012·Biotechnology Journal

Abstract

Despite the efforts that bioengineers have exerted in designing and constructing biological processes that function according to a predetermined set of rules, their operation remains fundamentally circumstantial. The contextual situation in which molecules and single‐celled or multi‐cellular organisms find themselves shapes the way they interact, respond to the environment and process external information. Since the birth of the field, synthetic biologists have had to grapple with contextual issues, particularly when the molecular and genetic devices inexplicably fail to function as designed when tested in vivo. In this review, we set out to identify and classify the sources of the unexpected divergences between design and actual function of synthetic systems and analyze possible methodologies aimed at controlling, if not preventing, unwanted contextual issues.

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Metadata

Authors
Cardinale, S., & Arkin, A. P.
Venue
Biotechnology Journal
Publisher
Wiley
Published
2012-05-31
Volume
7
Issue
7
Pages
856-866
ISSN
  • 1860-6768 (ISSN-L)
  • 1860-7314
OpenAlex
W2037913229
Cited by
449
References
6
FWCI
10.69
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Contextualizing context for synthetic biology – identifying causes of failure of synthetic biological systems. https://app.cochat.ai/papers/10.1002/biot.201200085
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Cardinale, S., & Arkin, A. P. (2012). Contextualizing context for synthetic biology – identifying causes of failure of synthetic biological systems. Biotechnology Journal. https://doi.org/10.1002/biot.201200085

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.