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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RosettaRemodel: A Generalized Framework for Flexible Backbone Protein Design
|
|---|---|
| Published in |
PLOS ONE, August 2011
|
| DOI | 10.1371/journal.pone.0024109 |
| Pubmed ID | |
| Authors |
Po-Ssu Huang, Yih-En Andrew Ban, Florian Richter, Ingemar Andre, Robert Vernon, William R. Schief, David Baker |
| Abstract |
We describe RosettaRemodel, a generalized framework for flexible protein design that provides a versatile and convenient interface to the Rosetta modeling suite. RosettaRemodel employs a unified interface, called a blueprint, which allows detailed control over many aspects of flexible backbone protein design calculations. RosettaRemodel allows the construction and elaboration of customized protocols for a wide range of design problems ranging from loop insertion and deletion, disulfide engineering, domain assembly, loop remodeling, motif grafting, symmetrical units, to de novo structure modeling. |
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 % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 388 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 2% |
| United Kingdom | 2 | <1% |
| Canada | 2 | <1% |
| India | 1 | <1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Unknown | 373 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 108 | 28% |
| Researcher | 82 | 21% |
| Student > Master | 38 | 10% |
| Student > Bachelor | 30 | 8% |
| Student > Postgraduate | 21 | 5% |
| Other | 48 | 12% |
| Unknown | 61 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 108 | 28% |
| Agricultural and Biological Sciences | 106 | 27% |
| Chemistry | 45 | 12% |
| Computer Science | 17 | 4% |
| Engineering | 11 | 3% |
| Other | 32 | 8% |
| Unknown | 69 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 12 July 2023.
All research outputs
#7,496,248
of 24,169,085 outputs
Outputs from PLOS ONE
#94,486
of 207,783 outputs
Outputs of similar age
#41,219
of 127,835 outputs
Outputs of similar age from PLOS ONE
#925
of 2,541 outputs
Altmetric has tracked 24,169,085 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 207,783 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has gotten more attention than average, scoring higher than 53% 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 127,835 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 2,541 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 60% of its contemporaries.