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Transcriptome-wide comparison of sequence variation in divergent ecotypes of kokanee salmon

Overview of attention for article published in BMC Genomics, May 2013
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Citations

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Title
Transcriptome-wide comparison of sequence variation in divergent ecotypes of kokanee salmon
Published in
BMC Genomics, May 2013
DOI 10.1186/1471-2164-14-308
Pubmed ID
Authors

Matthew A Lemay, David J Donnelly, Michael A Russello

Abstract

High throughput next-generation sequencing technology has enabled the collection of genome-wide sequence data and revolutionized single nucleotide polymorphism (SNP) discovery in a broad range of species. When analyzed within a population genomics framework, SNP-based genotypic data may be used to investigate questions of evolutionary, ecological, and conservation significance in natural populations of non-model organisms. Kokanee salmon are recently diverged freshwater populations of sockeye salmon (Oncorhynchus nerka) that exhibit reproductive ecotypes (stream-spawning and shore-spawning) in lakes throughout western North America and northeast Asia. Current conservation and management strategies may treat these ecotypes as discrete stocks, however their recent divergence and low levels of gene flow make in-season genetic stock identification a challenge. The development of genome-wide SNP markers is an essential step towards fine-scale stock identification, and may enable a direct investigation of the genetic basis of ecotype divergence.

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X Demographics

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

Geographical breakdown

Country Count As %
Canada 2 4%
Ireland 1 2%
Sweden 1 2%
Australia 1 2%
South Africa 1 2%
United States 1 2%
Unknown 50 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 25%
Researcher 11 19%
Student > Master 9 16%
Professor 4 7%
Student > Bachelor 3 5%
Other 12 21%
Unknown 4 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 70%
Biochemistry, Genetics and Molecular Biology 7 12%
Environmental Science 2 4%
Unspecified 1 2%
Immunology and Microbiology 1 2%
Other 1 2%
Unknown 5 9%
Attention Score in Context

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 29 May 2013.
All research outputs
#16,721,717
of 25,374,647 outputs
Outputs from BMC Genomics
#6,569
of 11,244 outputs
Outputs of similar age
#125,441
of 205,285 outputs
Outputs of similar age from BMC Genomics
#103
of 170 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 36th percentile – i.e., 36% 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 205,285 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 170 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.