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End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

Overview of attention for article published in Journal of Biological Engineering, February 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#26 of 288)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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27 X users
facebook
4 Facebook pages

Citations

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60 Dimensions

Readers on

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180 Mendeley
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Title
End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis
Published in
Journal of Biological Engineering, February 2016
DOI 10.1186/s13036-016-0024-5
Pubmed ID
Authors

Gregory Linshiz, Erik Jensen, Nina Stawski, Changhao Bi, Nick Elsbree, Hong Jiao, Jungkyu Kim, Richard Mathies, Jay D. Keasling, Nathan J. Hillson

Abstract

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Herein, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform's capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, and proteogenic and metabolic output analysis. Taken together, we demonstrate the microfluidic platform's potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 2 1%
Taiwan 1 <1%
Uruguay 1 <1%
China 1 <1%
United States 1 <1%
Unknown 174 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 22%
Researcher 38 21%
Student > Master 23 13%
Student > Bachelor 18 10%
Other 14 8%
Other 23 13%
Unknown 24 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 55 31%
Agricultural and Biological Sciences 35 19%
Engineering 31 17%
Chemical Engineering 7 4%
Computer Science 5 3%
Other 18 10%
Unknown 29 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2016.
All research outputs
#1,825,738
of 24,255,619 outputs
Outputs from Journal of Biological Engineering
#26
of 288 outputs
Outputs of similar age
#32,935
of 405,624 outputs
Outputs of similar age from Journal of Biological Engineering
#2
of 6 outputs
Altmetric has tracked 24,255,619 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 288 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 405,624 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.