↓ Skip to main content

Optimizing the genetic prediction of the eye and hair color for North Eurasian populations

Overview of attention for article published in BMC Genomics, September 2020
Altmetric Badge

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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
2 news outlets
twitter
5 X users

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
25 Mendeley
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
Optimizing the genetic prediction of the eye and hair color for North Eurasian populations
Published in
BMC Genomics, September 2020
DOI 10.1186/s12864-020-06923-1
Pubmed ID
Authors

Elena Balanovska, Elena Lukianova, Janet Kagazezheva, Andrey Maurer, Natalia Leybova, Anastasiya Agdzhoyan, Igor Gorin, Valeria Petrushenko, Maxat Zhabagin, Vladimir Pylev, Elena Kostryukova, Oleg Balanovsky

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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 16%
Student > Master 3 12%
Student > Ph. D. Student 3 12%
Student > Bachelor 3 12%
Lecturer > Senior Lecturer 1 4%
Other 1 4%
Unknown 10 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 28%
Agricultural and Biological Sciences 2 8%
Engineering 2 8%
Chemistry 1 4%
Unspecified 1 4%
Other 0 0%
Unknown 12 48%
Attention Score in Context

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 08 February 2024.
All research outputs
#2,252,834
of 25,335,657 outputs
Outputs from BMC Genomics
#584
of 11,220 outputs
Outputs of similar age
#57,156
of 408,913 outputs
Outputs of similar age from BMC Genomics
#13
of 167 outputs
Altmetric has tracked 25,335,657 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,220 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 94% 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 408,913 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 85% of its contemporaries.
We're also able to compare this research output to 167 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 92% of its contemporaries.