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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

blogs
1 blog
twitter
5 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
34 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Italy 1 3%
Luxembourg 1 3%
Unknown 31 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Researcher 7 21%
Professor > Associate Professor 5 15%
Student > Bachelor 4 12%
Student > Master 2 6%
Other 2 6%
Unknown 6 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 29%
Biochemistry, Genetics and Molecular Biology 7 21%
Computer Science 5 15%
Medicine and Dentistry 3 9%
Engineering 2 6%
Other 1 3%
Unknown 6 18%
Attention Score in Context

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
#3,268,720
of 22,766,595 outputs
Outputs from BMC Genomics
#1,277
of 10,639 outputs
Outputs of similar age
#39,314
of 256,089 outputs
Outputs of similar age from BMC Genomics
#20
of 211 outputs
Altmetric has tracked 22,766,595 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,639 research outputs from this source. They receive a mean Attention Score of 4.7. 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 256,089 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 84% of its contemporaries.
We're also able to compare this research output to 211 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.