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GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Overview of attention for article published in BMC Bioinformatics, February 2009
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
1 tweeter
patent
2 patents

Citations

dimensions_citation
1938 Dimensions

Readers on

mendeley
1578 Mendeley
citeulike
22 CiteULike
connotea
2 Connotea
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Title
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Published in
BMC Bioinformatics, February 2009
DOI 10.1186/1471-2105-10-48
Pubmed ID
Authors

Eran Eden, Roy Navon, Israel Steinfeld, Doron Lipson, Zohar Yakhini

Abstract

Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results.

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 1,578 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 31 2%
Germany 11 <1%
United Kingdom 9 <1%
Spain 6 <1%
Brazil 5 <1%
India 4 <1%
Canada 4 <1%
Belgium 4 <1%
Switzerland 4 <1%
Other 34 2%
Unknown 1466 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 488 31%
Researcher 353 22%
Student > Master 191 12%
Student > Bachelor 124 8%
Student > Doctoral Student 80 5%
Other 217 14%
Unknown 125 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 680 43%
Biochemistry, Genetics and Molecular Biology 401 25%
Medicine and Dentistry 92 6%
Computer Science 76 5%
Neuroscience 39 2%
Other 119 8%
Unknown 171 11%

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 16 January 2020.
All research outputs
#4,214,921
of 15,432,515 outputs
Outputs from BMC Bioinformatics
#1,794
of 5,639 outputs
Outputs of similar age
#60,703
of 235,008 outputs
Outputs of similar age from BMC Bioinformatics
#91
of 287 outputs
Altmetric has tracked 15,432,515 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 5,639 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 66% 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 235,008 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 73% of its contemporaries.
We're also able to compare this research output to 287 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.