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PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

Overview of attention for article published in PLOS ONE, July 2009
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Mentioned by

patent
1 patent

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
53 Mendeley
citeulike
2 CiteULike
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Title
PSPP: A Protein Structure Prediction Pipeline for Computing Clusters
Published in
PLOS ONE, July 2009
DOI 10.1371/journal.pone.0006254
Pubmed ID
Authors

Michael S. Lee, Rajkumar Bondugula, Valmik Desai, Nela Zavaljevski, In-Chul Yeh, Anders Wallqvist, Jaques Reifman

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 3 6%
Switzerland 2 4%
United States 2 4%
United Kingdom 1 2%
India 1 2%
Unknown 44 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 32%
Student > Ph. D. Student 13 25%
Student > Bachelor 8 15%
Professor > Associate Professor 4 8%
Student > Master 3 6%
Other 6 11%
Unknown 2 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 49%
Computer Science 4 8%
Medicine and Dentistry 4 8%
Social Sciences 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 11 21%
Unknown 3 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 31 January 2017.
All research outputs
#7,566,705
of 23,081,466 outputs
Outputs from PLOS ONE
#90,807
of 196,790 outputs
Outputs of similar age
#37,439
of 110,866 outputs
Outputs of similar age from PLOS ONE
#245
of 506 outputs
Altmetric has tracked 23,081,466 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 196,790 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one is in the 49th percentile – i.e., 49% 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 110,866 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 506 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.