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Visualising associations between paired ‘omics’ data sets

Overview of attention for article published in BioData Mining, November 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#31 of 244)
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog
twitter
15 tweeters

Citations

dimensions_citation
119 Dimensions

Readers on

mendeley
317 Mendeley
citeulike
6 CiteULike
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Title
Visualising associations between paired ‘omics’ data sets
Published in
BioData Mining, November 2012
DOI 10.1186/1756-0381-5-19
Pubmed ID
Authors

Ignacio González, Kim-Anh Lê Cao, Melissa J Davis, Sébastien Déjean

Abstract

Each omics platform is now able to generate a large amount of data. Genomics, proteomics, metabolomics, interactomics are compiled at an ever increasing pace and now form a core part of the fundamental systems biology framework. Recently, several integrative approaches have been proposed to extract meaningful information. However, these approaches lack of visualisation outputs to fully unravel the complex associations between different biological entities.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 317 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
Belgium 3 <1%
Brazil 3 <1%
France 2 <1%
Sweden 2 <1%
Netherlands 2 <1%
South Africa 1 <1%
Italy 1 <1%
Australia 1 <1%
Other 9 3%
Unknown 288 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 98 31%
Student > Ph. D. Student 79 25%
Student > Master 26 8%
Student > Doctoral Student 21 7%
Student > Bachelor 17 5%
Other 51 16%
Unknown 25 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 124 39%
Biochemistry, Genetics and Molecular Biology 43 14%
Computer Science 21 7%
Medicine and Dentistry 19 6%
Mathematics 15 5%
Other 49 15%
Unknown 46 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 04 June 2019.
All research outputs
#1,168,687
of 15,175,259 outputs
Outputs from BioData Mining
#31
of 244 outputs
Outputs of similar age
#10,848
of 151,149 outputs
Outputs of similar age from BioData Mining
#3
of 16 outputs
Altmetric has tracked 15,175,259 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 244 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done well, scoring higher than 87% 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 151,149 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 92% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.