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Attention Score in Context
Chapter title |
Enzyme Evolution by Yeast Cell Surface Engineering.
|
---|---|
Chapter number | 12 |
Book title |
Yeast Surface Display
|
Published in |
Methods in molecular biology, January 2015
|
DOI | 10.1007/978-1-4939-2748-7_12 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2747-0, 978-1-4939-2748-7
|
Authors |
Miura, Natsuko, Kuroda, Kouichi, Ueda, Mitsuyoshi, Natsuko Miura, Kouichi Kuroda, Mitsuyoshi Ueda |
Abstract |
Artificial evolution of proteins with the aim of acquiring novel or improved functionality is important for practical applications of the proteins. We have developed yeast cell surface engineering methods (or arming technology) for evolving enzymes. Here, we have described yeast cell surface engineering coupled with in vivo homologous recombination and library screening as a method for the artificial evolution of enzymes such as firefly luciferases. Using this method, novel luciferases with improved substrate specificity and substrate reactivity were engineered. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 11% |
Unknown | 8 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 56% |
Student > Ph. D. Student | 1 | 11% |
Professor | 1 | 11% |
Student > Master | 1 | 11% |
Professor > Associate Professor | 1 | 11% |
Other | 0 | 0% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 4 | 44% |
Biochemistry, Genetics and Molecular Biology | 2 | 22% |
Engineering | 1 | 11% |
Unknown | 2 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 16 March 2016.
All research outputs
#14,815,222
of 22,811,321 outputs
Outputs from Methods in molecular biology
#4,686
of 13,119 outputs
Outputs of similar age
#198,003
of 353,098 outputs
Outputs of similar age from Methods in molecular biology
#296
of 996 outputs
Altmetric has tracked 22,811,321 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,119 research outputs from this source. They receive a mean Attention Score of 3.3. This one has gotten more attention than average, scoring higher than 59% 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 353,098 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 996 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.