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VAS: a convenient web portal for efficient integration of genomic features with millions of genetic variants

Overview of attention for article published in BMC Genomics, October 2014
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog
twitter
5 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
32 Mendeley
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Title
VAS: a convenient web portal for efficient integration of genomic features with millions of genetic variants
Published in
BMC Genomics, October 2014
DOI 10.1186/1471-2164-15-886
Pubmed ID
Authors

Eric Dun Ho, Qin Cao, Sau Dan Lee, Kevin Y Yip

Abstract

High-throughput experimental methods have fostered the systematic detection of millions of genetic variants from any human genome. To help explore the potential biological implications of these genetic variants, software tools have been previously developed for integrating various types of information about these genomic regions from multiple data sources. Most of these tools were designed either for studying a small number of variants at a time, or for local execution on powerful machines.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 6%
United States 1 3%
Luxembourg 1 3%
Unknown 28 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Researcher 7 22%
Professor > Associate Professor 5 16%
Student > Bachelor 4 13%
Student > Master 2 6%
Other 2 6%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 34%
Biochemistry, Genetics and Molecular Biology 7 22%
Computer Science 5 16%
Medicine and Dentistry 3 9%
Engineering 2 6%
Other 1 3%
Unknown 3 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 October 2014.
All research outputs
#1,452,904
of 12,373,620 outputs
Outputs from BMC Genomics
#814
of 7,313 outputs
Outputs of similar age
#30,227
of 217,334 outputs
Outputs of similar age from BMC Genomics
#7
of 32 outputs
Altmetric has tracked 12,373,620 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,313 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 88% 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 217,334 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 32 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.