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Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests

Overview of attention for article published in BMC Genomics, January 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
3 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
63 Dimensions

Readers on

mendeley
136 Mendeley
citeulike
1 CiteULike

What is this page?

Summary Twitter Facebook Google+ Dimensions citations
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Title
Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests
Published in
BMC Genomics, January 2015
DOI 10.1186/1471-2164-16-s2-s5
Pubmed ID
25708662
Authors

Thanh-Tung Nguyen, Joshua Zhexue Huang, Qingyao Wu, Thuy Thi Nguyen, Mark Junjie Li

View on publisher site

Twitter Demographics

The data shown below were collected from the profiles of 3 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 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Colombia 1 <1%
United States 1 <1%
Thailand 1 <1%
Unknown 132 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 26%
Researcher 26 19%
Student > Master 24 18%
Student > Bachelor 8 6%
Student > Doctoral Student 8 6%
Other 16 12%
Unknown 18 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 21%
Computer Science 27 20%
Biochemistry, Genetics and Molecular Biology 22 16%
Medicine and Dentistry 9 7%
Neuroscience 4 3%
Other 20 15%
Unknown 26 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 November 2018.
All research outputs
#7,305,530
of 13,851,031 outputs
Outputs from BMC Genomics
#3,486
of 8,136 outputs
Outputs of similar age
#102,942
of 280,635 outputs
Outputs of similar age from BMC Genomics
#57
of 166 outputs
Altmetric has tracked 13,851,031 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,136 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 55% 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 280,635 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 166 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.

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