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A comparison of statistical methods for genomic selection in a mice population

Overview of attention for article published in BMC Genetics, January 2012
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
48 Dimensions

Readers on

mendeley
198 Mendeley
Title
A comparison of statistical methods for genomic selection in a mice population
Published in
BMC Genetics, January 2012
DOI 10.1186/1471-2156-13-100
Pubmed ID
Authors

Haroldo HR Neves, Roberto Carvalheiro, Sandra A Queiroz

Abstract

The availability of high-density panels of SNP markers has opened new perspectives for marker-assisted selection strategies, such that genotypes for these markers are used to predict the genetic merit of selection candidates. Because the number of markers is often much larger than the number of phenotypes, marker effect estimation is not a trivial task. The objective of this research was to compare the predictive performance of ten different statistical methods employed in genomic selection, by analyzing data from a heterogeneous stock mice population.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 198 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Russia 1 <1%
Brazil 1 <1%
Spain 1 <1%
Indonesia 1 <1%
Unknown 189 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 25%
Researcher 47 24%
Student > Master 27 14%
Student > Doctoral Student 18 9%
Student > Bachelor 7 4%
Other 21 11%
Unknown 29 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 125 63%
Biochemistry, Genetics and Molecular Biology 16 8%
Mathematics 6 3%
Computer Science 6 3%
Medicine and Dentistry 4 2%
Other 9 5%
Unknown 32 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 November 2012.
All research outputs
#6,706,575
of 12,372,276 outputs
Outputs from BMC Genetics
#301
of 828 outputs
Outputs of similar age
#60,413
of 137,068 outputs
Outputs of similar age from BMC Genetics
#4
of 12 outputs
Altmetric has tracked 12,372,276 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 828 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 60% 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 137,068 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 54% of its contemporaries.
We're also able to compare this research output to 12 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 66% of its contemporaries.