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Using Unnatural Protein Fusions to Engineer a Coenzyme Self-Sufficiency System for D-Phenyllactic Acid Biosynthesis in Escherichia coli

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, December 2021
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

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4 Mendeley
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Title
Using Unnatural Protein Fusions to Engineer a Coenzyme Self-Sufficiency System for D-Phenyllactic Acid Biosynthesis in Escherichia coli
Published in
Frontiers in Bioengineering and Biotechnology, December 2021
DOI 10.3389/fbioe.2021.795885
Pubmed ID
Authors

Zhao Qin, Dan Wang, Ruoshi Luo, Tinglan Li, Xiaochao Xiong, Peng Chen

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 25%
Researcher 1 25%
Unknown 2 50%
Readers by discipline Count As %
Chemistry 2 50%
Unknown 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 December 2021.
All research outputs
#20,194,150
of 22,711,242 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#4,559
of 6,496 outputs
Outputs of similar age
#379,754
of 466,115 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#311
of 537 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,496 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% 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 466,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 537 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.