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An estimate is worth about a thousand experiments: using order-of-magnitude estimates to identify cellular engineering targets

Overview of attention for article published in Microbial Cell Factories, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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17 X users

Citations

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32 Mendeley
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Title
An estimate is worth about a thousand experiments: using order-of-magnitude estimates to identify cellular engineering targets
Published in
Microbial Cell Factories, August 2018
DOI 10.1186/s12934-018-0979-7
Pubmed ID
Authors

Kevin James Metcalf, Marilyn F. Slininger Lee, Christopher Matthew Jakobson, Danielle Tullman-Ercek

Abstract

Biotechnological processes use microbes to convert abundant molecules, such as glucose, into high-value products, such as pharmaceuticals, commodity and fine chemicals, and energy. However, from the outset of the development of a new bioprocess, it is difficult to determine the feasibility, expected yields, and targets for engineering. In this review, we describe a methodology that uses rough estimates to assess the feasibility of a process, approximate the expected product titer of a biological system, and identify variables to manipulate in order to achieve the desired performance. This methodology uses estimates from literature and biological intuition, and can be applied in the early stages of a project to help plan future engineering. We highlight recent literature examples, as well as two case studies from our own work, to demonstrate the use and power of rough estimates. Describing and predicting biological function using estimates guides the research and development phase of new bioprocesses and is a useful first step to understand and build a new microbial factory.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 28%
Student > Ph. D. Student 7 22%
Student > Bachelor 2 6%
Student > Master 2 6%
Student > Doctoral Student 1 3%
Other 4 13%
Unknown 7 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 31%
Agricultural and Biological Sciences 7 22%
Engineering 4 13%
Chemical Engineering 1 3%
Chemistry 1 3%
Other 1 3%
Unknown 8 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 07 September 2018.
All research outputs
#3,304,182
of 23,102,082 outputs
Outputs from Microbial Cell Factories
#145
of 1,618 outputs
Outputs of similar age
#68,613
of 334,794 outputs
Outputs of similar age from Microbial Cell Factories
#3
of 32 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,618 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 90% 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 334,794 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.