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Phylogenetic reconstruction of ancestral character states for gene expression and mRNA splicing data

Overview of attention for article published in BMC Bioinformatics, May 2005
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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 (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
1 tweeter
patent
1 patent
wikipedia
1 Wikipedia page

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
49 Mendeley
citeulike
3 CiteULike
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Title
Phylogenetic reconstruction of ancestral character states for gene expression and mRNA splicing data
Published in
BMC Bioinformatics, May 2005
DOI 10.1186/1471-2105-6-127
Pubmed ID
Authors

Roald Rossnes, Ingvar Eidhammer, David A Liberles

Abstract

As genomes evolve after speciation, gene content, coding sequence, gene expression, and splicing all diverge with time from ancestors with close relatives. A minimum evolution general method for continuous character analysis in a phylogenetic perspective is presented that allows for reconstruction of ancestral character states and for measuring along branch evolution.

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 49 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%
Netherlands 1 2%
Australia 1 2%
United Kingdom 1 2%
Mexico 1 2%
China 1 2%
United States 1 2%
Unknown 41 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 31%
Researcher 8 16%
Student > Master 7 14%
Professor > Associate Professor 3 6%
Student > Bachelor 2 4%
Other 9 18%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 73%
Biochemistry, Genetics and Molecular Biology 4 8%
Computer Science 3 6%
Unknown 6 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 02 April 2020.
All research outputs
#3,348,856
of 17,351,915 outputs
Outputs from BMC Bioinformatics
#1,412
of 6,150 outputs
Outputs of similar age
#50,873
of 273,900 outputs
Outputs of similar age from BMC Bioinformatics
#94
of 422 outputs
Altmetric has tracked 17,351,915 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,150 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 76% 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 273,900 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 81% of its contemporaries.
We're also able to compare this research output to 422 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.