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Screening large-scale association study data: exploiting interactions using random forests

Overview of attention for article published in BMC Genomic Data, December 2004
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Mentioned by

f1000
1 research highlight platform

Citations

dimensions_citation
372 Dimensions

Readers on

mendeley
295 Mendeley
citeulike
2 CiteULike
connotea
1 Connotea
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Title
Screening large-scale association study data: exploiting interactions using random forests
Published in
BMC Genomic Data, December 2004
DOI 10.1186/1471-2156-5-32
Pubmed ID
Authors

Kathryn L Lunetta, L Brooke Hayward, Jonathan Segal, Paul Van Eerdewegh

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 295 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 5%
Germany 3 1%
United Kingdom 2 <1%
Italy 2 <1%
Switzerland 1 <1%
Brazil 1 <1%
Israel 1 <1%
Turkey 1 <1%
Canada 1 <1%
Other 3 1%
Unknown 266 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 22%
Researcher 52 18%
Student > Master 44 15%
Professor > Associate Professor 21 7%
Student > Bachelor 19 6%
Other 49 17%
Unknown 45 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 82 28%
Computer Science 31 11%
Mathematics 28 9%
Medicine and Dentistry 23 8%
Biochemistry, Genetics and Molecular Biology 22 7%
Other 59 20%
Unknown 50 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 11 January 2005.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from BMC Genomic Data
#668
of 1,204 outputs
Outputs of similar age
#128,569
of 149,814 outputs
Outputs of similar age from BMC Genomic Data
#1
of 2 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 149,814 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them