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Comparison of lists of genes based on functional profiles

Overview of attention for article published in BMC Bioinformatics, October 2011
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
twitter
3 X users
googleplus
1 Google+ user

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
88 Mendeley
citeulike
13 CiteULike
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Title
Comparison of lists of genes based on functional profiles
Published in
BMC Bioinformatics, October 2011
DOI 10.1186/1471-2105-12-401
Pubmed ID
Authors

Miquel Salicrú, Jordi Ocaña, Alex Sánchez-Pla

Abstract

How to compare studies on the basis of their biological significance is a problem of central importance in high-throughput genomics. Many methods for performing such comparisons are based on the information in databases of functional annotation, such as those that form the Gene Ontology (GO). Typically, they consist of analyzing gene annotation frequencies in some pre-specified GO classes, in a class-by-class way, followed by p-value adjustment for multiple testing. Enrichment analysis, where a list of genes is compared against a wider universe of genes, is the most common example.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
Portugal 1 1%
Malaysia 1 1%
Brazil 1 1%
United Kingdom 1 1%
Argentina 1 1%
Belgium 1 1%
Russia 1 1%
Spain 1 1%
Other 2 2%
Unknown 75 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 40%
Student > Ph. D. Student 18 20%
Professor > Associate Professor 6 7%
Student > Master 6 7%
Student > Postgraduate 5 6%
Other 13 15%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 53%
Biochemistry, Genetics and Molecular Biology 16 18%
Computer Science 8 9%
Mathematics 5 6%
Unspecified 1 1%
Other 4 5%
Unknown 7 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 14 November 2011.
All research outputs
#2,667,316
of 22,653,392 outputs
Outputs from BMC Bioinformatics
#883
of 7,236 outputs
Outputs of similar age
#14,537
of 136,901 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 102 outputs
Altmetric has tracked 22,653,392 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,236 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 87% 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 136,901 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 89% of its contemporaries.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.