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Genome wide analysis reveals single nucleotide polymorphisms associated with fatness and putative novel copy number variants in three pig breeds

Overview of attention for article published in BMC Genomics, November 2013
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Title
Genome wide analysis reveals single nucleotide polymorphisms associated with fatness and putative novel copy number variants in three pig breeds
Published in
BMC Genomics, November 2013
DOI 10.1186/1471-2164-14-784
Pubmed ID
Authors

Katie E Fowler, Ricardo Pong-Wong, Julien Bauer, Emily J Clemente, Christopher P Reitter, Nabeel A Affara, Stephen Waite, Grant A Walling, Darren K Griffin

Abstract

Obesity, excess fat tissue in the body, can underlie a variety of medical complaints including heart disease, stroke and cancer. The pig is an excellent model organism for the study of various human disorders, including obesity, as well as being the foremost agricultural species. In order to identify genetic variants associated with fatness, we used a selective genomic approach sampling DNA from animals at the extreme ends of the fat and lean spectrum using estimated breeding values derived from a total population size of over 70,000 animals. DNA from 3 breeds (Sire Line Large White, Duroc and a white Pietrain composite line (Titan)) was used to interrogate the Illumina Porcine SNP60 Genotyping Beadchip in order to identify significant associations in terms of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs).

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The data shown below were collected from the profile of 1 X user 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Student > Ph. D. Student 8 13%
Student > Bachelor 8 13%
Student > Master 6 10%
Student > Doctoral Student 5 8%
Other 9 15%
Unknown 15 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 37%
Biochemistry, Genetics and Molecular Biology 6 10%
Medicine and Dentistry 4 6%
Engineering 2 3%
Nursing and Health Professions 2 3%
Other 4 6%
Unknown 21 34%
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 13 November 2013.
All research outputs
#15,284,663
of 22,729,647 outputs
Outputs from BMC Genomics
#6,667
of 10,628 outputs
Outputs of similar age
#130,421
of 212,391 outputs
Outputs of similar age from BMC Genomics
#74
of 155 outputs
Altmetric has tracked 22,729,647 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,628 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% 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 212,391 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.