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Attention Score in Context
Chapter title |
Computational Introduction of Catalytic Activity into Proteins.
|
---|---|
Chapter number | 13 |
Book title |
Computational Design of Ligand Binding Proteins
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3569-7_13 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3567-3, 978-1-4939-3569-7
|
Authors |
Steve J. Bertolani, Dylan Alexander Carlin, Justin B. Siegel |
Editors |
Barry L. Stoddard |
Abstract |
Recently, there have been several successful cases of introducing catalytic activity into proteins. One method that has been used successfully to achieve this is the theozyme placement and enzyme design algorithms implemented in Rosetta Molecular Modeling Suite. Here, we illustrate how to use this software to recapitulate the placement of catalytic residues and ligand into a protein using a theozyme, protein scaffold, and catalytic constraints as input. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 10 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 4 | 40% |
Student > Bachelor | 2 | 20% |
Student > Ph. D. Student | 1 | 10% |
Professor | 1 | 10% |
Student > Master | 1 | 10% |
Other | 1 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 5 | 50% |
Chemistry | 2 | 20% |
Agricultural and Biological Sciences | 1 | 10% |
Business, Management and Accounting | 1 | 10% |
Neuroscience | 1 | 10% |
Other | 1 | 10% |
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 27 April 2016.
All research outputs
#18,453,763
of 22,865,319 outputs
Outputs from Methods in molecular biology
#7,923
of 13,127 outputs
Outputs of similar age
#284,496
of 393,648 outputs
Outputs of similar age from Methods in molecular biology
#846
of 1,470 outputs
Altmetric has tracked 22,865,319 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,127 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% 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 393,648 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.