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Selection of organisms for the co-evolution-based study of protein interactions

Overview of attention for article published in BMC Bioinformatics, September 2011
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Title
Selection of organisms for the co-evolution-based study of protein interactions
Published in
BMC Bioinformatics, September 2011
DOI 10.1186/1471-2105-12-363
Pubmed ID
Authors

Dorota Herman, David Ochoa, David Juan, Daniel Lopez, Alfonso Valencia, Florencio Pazos

Abstract

The prediction and study of protein interactions and functional relationships based on similarity of phylogenetic trees, exemplified by the mirrortree and related methodologies, is being widely used. Although dependence between the performance of these methods and the set of organisms used to build the trees was suspected, so far nobody assessed it in an exhaustive way, and, in general, previous works used as many organisms as possible. In this work we asses the effect of using different sets of organism (chosen according with various phylogenetic criteria) on the performance of this methodology in detecting protein interactions of different nature.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
Spain 4 6%
Germany 1 1%
Italy 1 1%
Switzerland 1 1%
Netherlands 1 1%
China 1 1%
Unknown 59 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 33%
Student > Ph. D. Student 15 21%
Other 6 8%
Student > Bachelor 5 7%
Student > Master 5 7%
Other 13 18%
Unknown 4 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 60%
Biochemistry, Genetics and Molecular Biology 15 21%
Computer Science 6 8%
Mathematics 1 1%
Environmental Science 1 1%
Other 2 3%
Unknown 4 6%
Attention Score in Context

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 18 February 2015.
All research outputs
#14,676,511
of 22,792,160 outputs
Outputs from BMC Bioinformatics
#5,019
of 7,280 outputs
Outputs of similar age
#85,982
of 126,169 outputs
Outputs of similar age from BMC Bioinformatics
#65
of 86 outputs
Altmetric has tracked 22,792,160 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 126,169 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 86 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.