↓ Skip to main content

The Ensembl Variant Effect Predictor

Overview of attention for article published in Genome Biology, June 2016
Altmetric Badge

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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
6 news outlets
blogs
3 blogs
twitter
70 X users
patent
3 patents
peer_reviews
1 peer review site
wikipedia
2 Wikipedia pages
googleplus
1 Google+ user
video
1 YouTube creator

Citations

dimensions_citation
5288 Dimensions

Readers on

mendeley
3380 Mendeley
citeulike
9 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The Ensembl Variant Effect Predictor
Published in
Genome Biology, June 2016
DOI 10.1186/s13059-016-0974-4
Pubmed ID
Authors

William McLaren, Laurent Gil, Sarah E. Hunt, Harpreet Singh Riat, Graham R. S. Ritchie, Anja Thormann, Paul Flicek, Fiona Cunningham

Abstract

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 70 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 3,380 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 <1%
United Kingdom 3 <1%
Netherlands 1 <1%
Chile 1 <1%
Norway 1 <1%
Italy 1 <1%
Uruguay 1 <1%
Germany 1 <1%
Sweden 1 <1%
Other 3 <1%
Unknown 3359 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 626 19%
Researcher 558 17%
Student > Master 402 12%
Student > Bachelor 341 10%
Student > Doctoral Student 172 5%
Other 421 12%
Unknown 860 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1086 32%
Agricultural and Biological Sciences 583 17%
Medicine and Dentistry 262 8%
Computer Science 124 4%
Neuroscience 48 1%
Other 297 9%
Unknown 980 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 112. 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 13 February 2024.
All research outputs
#375,606
of 25,481,734 outputs
Outputs from Genome Biology
#180
of 4,480 outputs
Outputs of similar age
#7,418
of 355,821 outputs
Outputs of similar age from Genome Biology
#5
of 82 outputs
Altmetric has tracked 25,481,734 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,480 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 96% 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 355,821 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 97% of its contemporaries.
We're also able to compare this research output to 82 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 95% of its contemporaries.