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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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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

blogs
2 blogs
twitter
3 tweeters

Readers on

mendeley
216 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 profiles of 3 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 216 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 4%
Germany 6 3%
France 3 1%
Canada 3 1%
United Kingdom 3 1%
China 2 <1%
Spain 2 <1%
Portugal 2 <1%
Bulgaria 1 <1%
Other 10 5%
Unknown 176 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 76 35%
Researcher 52 24%
Student > Master 36 17%
Professor > Associate Professor 13 6%
Student > Postgraduate 9 4%
Other 30 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 105 49%
Biochemistry, Genetics and Molecular Biology 40 19%
Computer Science 37 17%
Unspecified 7 3%
Mathematics 6 3%
Other 21 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 09 February 2018.
All research outputs
#565,601
of 9,179,047 outputs
Outputs from Bioinformatics
#485
of 6,292 outputs
Outputs of similar age
#551,054
of 8,538,810 outputs
Outputs of similar age from Bioinformatics
#465
of 5,693 outputs
Altmetric has tracked 9,179,047 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,292 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 92% 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 8,538,810 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 93% of its contemporaries.
We're also able to compare this research output to 5,693 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 91% of its contemporaries.