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Advances in analytical tools for high throughput strain engineering

Overview of attention for article published in Current Opinion in Biotechnology, February 2018
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Advances in analytical tools for high throughput strain engineering
Published in
Current Opinion in Biotechnology, February 2018
DOI 10.1016/j.copbio.2018.01.027
Pubmed ID
Authors

Esteban Marcellin, Lars Keld Nielsen

Abstract

The emergence of inexpensive, base-perfect genome editing is revolutionising biology. Modern industrial biotechnology exploits the advances in genome editing in combination with automation, analytics and data integration to build high-throughput automated strain engineering pipelines also known as biofoundries. Biofoundries replace the slow and inconsistent artisanal processes used to build microbial cell factories with an automated design-build-test cycle, considerably reducing the time needed to deliver commercially viable strains. Testing and hence learning remains relatively shallow, but recent advances in analytical chemistry promise to increase the depth of characterization possible. Analytics combined with models of cellular physiology in automated systems biology pipelines should enable deeper learning and hence a steeper pitch of the learning cycle. This review explores the progress, advances and remaining bottlenecks of analytical tools for high throughput strain engineering.

X Demographics

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The data shown below were collected from the profiles of 5 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 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 158 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 28%
Researcher 27 17%
Student > Master 13 8%
Student > Doctoral Student 11 7%
Student > Bachelor 7 4%
Other 16 10%
Unknown 39 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 34 22%
Agricultural and Biological Sciences 34 22%
Engineering 11 7%
Chemical Engineering 8 5%
Immunology and Microbiology 3 2%
Other 17 11%
Unknown 51 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 21 March 2018.
All research outputs
#14,283,318
of 25,382,440 outputs
Outputs from Current Opinion in Biotechnology
#2,089
of 2,751 outputs
Outputs of similar age
#218,794
of 454,408 outputs
Outputs of similar age from Current Opinion in Biotechnology
#35
of 56 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,751 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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 454,408 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.