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Models of gene gain and gene loss for probabilistic reconstruction of gene content in the last universal common ancestor of life

Overview of attention for article published in Biology Direct, December 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

news
1 news outlet
twitter
1 tweeter
video
1 video uploader

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
61 Mendeley
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Title
Models of gene gain and gene loss for probabilistic reconstruction of gene content in the last universal common ancestor of life
Published in
Biology Direct, December 2013
DOI 10.1186/1745-6150-8-32
Pubmed ID
Authors

Lavanya Kannan, Hua Li, Boris Rubinstein, Arcady Mushegian

Abstract

The problem of probabilistic inference of gene content in the last common ancestor of several extant species with completely sequenced genomes is: for each gene that is conserved in all or some of the genomes, assign the probability that its ancestral gene was present in the genome of their last common ancestor.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Switzerland 1 2%
Chile 1 2%
Russia 1 2%
Spain 1 2%
Unknown 56 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 28%
Student > Master 11 18%
Researcher 10 16%
Student > Bachelor 8 13%
Professor 4 7%
Other 8 13%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 48%
Biochemistry, Genetics and Molecular Biology 14 23%
Computer Science 5 8%
Immunology and Microbiology 2 3%
Mathematics 1 2%
Other 3 5%
Unknown 7 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 09 August 2020.
All research outputs
#2,477,540
of 18,623,929 outputs
Outputs from Biology Direct
#120
of 603 outputs
Outputs of similar age
#36,910
of 282,517 outputs
Outputs of similar age from Biology Direct
#9
of 24 outputs
Altmetric has tracked 18,623,929 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 603 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 79% 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 282,517 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 24 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 62% of its contemporaries.