GOSemSim: an R package for measuring semantic similarity among GO terms and gene products.

Overview of attention for article published in Bioinformatics, April 2010
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

blogs
2 blogs
twitter
1 tweeter

Readers on

mendeley
173 Mendeley
citeulike
11 CiteULike
connotea
4 Connotea
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Title
GOSemSim: an R package for measuring semantic similarity among GO terms and gene products.
Published in
Bioinformatics, April 2010
DOI 10.1093/bioinformatics/btq064
Pubmed ID
Authors

Guangchuang Yu, Fei Li, Yide Qin, Xiaochen Bo, Yibo Wu, Shengqi Wang, Yu, Guangchuang, Li, Fei, Qin, Yide, Bo, Xiaochen, Wu, Yibo, Wang, Shengqi

Abstract

The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. Four information content (IC)- and a graph-based methods are implemented in the GOSemSim package, multiple species including human, rat, mouse, fly and yeast are also supported. The functions provided by the GOSemSim offer flexibility for applications, and can be easily integrated into high-throughput analysis pipelines.

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 173 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 5%
Germany 5 3%
France 3 2%
Canada 3 2%
United Kingdom 3 2%
Italy 2 1%
China 2 1%
Spain 2 1%
Portugal 2 1%
Other 9 5%
Unknown 134 77%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 34%
Researcher 48 28%
Student > Master 31 18%
Professor > Associate Professor 12 7%
Student > Bachelor 6 3%
Other 18 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 99 57%
Computer Science 34 20%
Biochemistry, Genetics and Molecular Biology 20 12%
Mathematics 6 3%
Psychology 5 3%
Other 9 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 11 January 2017.
All research outputs
#416,475
of 7,534,762 outputs
Outputs from Bioinformatics
#451
of 5,426 outputs
Outputs of similar age
#405,578
of 6,920,390 outputs
Outputs of similar age from Bioinformatics
#427
of 4,723 outputs
Altmetric has tracked 7,534,762 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,426 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 91% 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 6,920,390 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 4,723 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.