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DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis

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

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
3 blogs
twitter
18 tweeters
facebook
2 Facebook pages

Readers on

mendeley
52 Mendeley
citeulike
2 CiteULike
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Title
DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis
Published in
Bioinformatics, February 2015
DOI 10.1093/bioinformatics/btu684
Pubmed ID
Authors

Guangchuang Yu, Li-Gen Wang, Guang-Rong Yan, Qing-Yu He, Yu G, Wang LG, Yan GR, He QY, Yu, Guangchuang, Wang, Li-Gen, Yan, Guang-Rong, He, Qing-Yu

Abstract

Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported.

Twitter Demographics

The data shown below were collected from the profiles of 18 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 8%
Germany 2 4%
United Kingdom 2 4%
Italy 1 2%
South Africa 1 2%
Brazil 1 2%
Denmark 1 2%
Taiwan 1 2%
Korea, Republic of 1 2%
Other 0 0%
Unknown 38 73%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 38%
Student > Ph. D. Student 14 27%
Student > Master 7 13%
Student > Postgraduate 3 6%
Professor > Associate Professor 3 6%
Other 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 52%
Computer Science 11 21%
Biochemistry, Genetics and Molecular Biology 6 12%
Medicine and Dentistry 3 6%
Engineering 2 4%
Other 3 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 08 June 2017.
All research outputs
#227,404
of 7,902,379 outputs
Outputs from Bioinformatics
#90
of 5,566 outputs
Outputs of similar age
#7,616
of 198,253 outputs
Outputs of similar age from Bioinformatics
#8
of 127 outputs
Altmetric has tracked 7,902,379 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,566 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 98% 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 198,253 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 96% of its contemporaries.
We're also able to compare this research output to 127 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 93% of its contemporaries.