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BACA: bubble chArt to compare annotations

Overview of attention for article published in BMC Bioinformatics, February 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
6 tweeters
peer_reviews
1 peer review site

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
39 Mendeley
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Title
BACA: bubble chArt to compare annotations
Published in
BMC Bioinformatics, February 2015
DOI 10.1186/s12859-015-0477-4
Pubmed ID
Authors

Vittorio Fortino, Harri Alenius, Dario Greco

Abstract

BackgroundDAVID is the most popular tool for interpreting large lists of gene/proteins classically produced in high-throughput experiments. However, the use of DAVID website becomes difficult when analyzing multiple gene lists, for it does not provide an adequate visualization tool to show/compare multiple enrichment results in a concise and informative manner.ResultWe implemented a new R-based graphical tool, BACA (Bubble chArt to Compare Annotations), which uses the DAVID web service for cross-comparing enrichment analysis results derived from multiple large gene lists. BACA is implemented in R and is freely available at the CRAN repository (http://cran.r-project.org/web/packages/BACA/).ConclusionThe package BACA allows R users to combine multiple annotation charts into one output graph by passing DAVID website.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 3%
Netherlands 1 3%
Norway 1 3%
Unknown 36 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 44%
Student > Ph. D. Student 8 21%
Student > Master 3 8%
Other 2 5%
Professor 2 5%
Other 6 15%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 38%
Biochemistry, Genetics and Molecular Biology 8 21%
Medicine and Dentistry 4 10%
Computer Science 4 10%
Environmental Science 1 3%
Other 4 10%
Unknown 3 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 August 2015.
All research outputs
#4,303,827
of 14,573,111 outputs
Outputs from BMC Bioinformatics
#1,969
of 5,420 outputs
Outputs of similar age
#78,372
of 282,422 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 42 outputs
Altmetric has tracked 14,573,111 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 5,420 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 62% 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 282,422 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 42 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 66% of its contemporaries.