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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Growth-Coupled Carotenoids Production Using Adaptive Laboratory Evolution
|
---|---|
Chapter number | 20 |
Book title |
Synthetic Metabolic Pathways
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7295-1_20 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7294-4, 978-1-4939-7295-1
|
Authors |
Luis H. Reyes, Katy C. Kao |
Abstract |
Adaptive laboratory evolution is a powerful technique for strain development. However, the target phenotypes using this strategy have been limited by the required coupling of the phenotype-of-interest with fitness or survival, and thus adaptive evolution is generally not used to improve product formation. If the desired product confers a benefit to the host, then adaptive evolution can be an effective approach to improve host productivity. In this book chapter, we describe an effective adaptive laboratory evolution strategy for improving product formation of carotenoids, a class of compounds with antioxidant potential, in the yeast Saccharomyces cerevisiae. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 23 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 30% |
Student > Master | 4 | 17% |
Student > Ph. D. Student | 3 | 13% |
Student > Bachelor | 3 | 13% |
Professor | 1 | 4% |
Other | 1 | 4% |
Unknown | 4 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 7 | 30% |
Agricultural and Biological Sciences | 7 | 30% |
Engineering | 2 | 9% |
Chemistry | 1 | 4% |
Computer Science | 1 | 4% |
Other | 0 | 0% |
Unknown | 5 | 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 08 December 2017.
All research outputs
#14,831,338
of 23,008,860 outputs
Outputs from Methods in molecular biology
#4,666
of 13,157 outputs
Outputs of similar age
#252,607
of 442,295 outputs
Outputs of similar age from Methods in molecular biology
#499
of 1,498 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 64% 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 442,295 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 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.