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High-throughput polymorphism detection and genotyping in Brassica napus using next-generation RAD sequencing

Overview of attention for article published in BMC Genomics, June 2012
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Title
High-throughput polymorphism detection and genotyping in Brassica napus using next-generation RAD sequencing
Published in
BMC Genomics, June 2012
DOI 10.1186/1471-2164-13-281
Pubmed ID
Authors

Anja Bus, Jochen Hecht, Bruno Huettel, Richard Reinhardt, Benjamin Stich

Abstract

The complex genome of rapeseed (Brassica napus) is not well understood despite the economic importance of the species. Good knowledge of sequence variation is needed for genetics approaches and breeding purposes. We used a diversity set of B. napus representing eight different germplasm types to sequence genome-wide distributed restriction-site associated DNA (RAD) fragments for polymorphism detection and genotyping.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 2%
United States 4 2%
Colombia 2 <1%
Chile 2 <1%
Brazil 2 <1%
United Kingdom 2 <1%
Indonesia 1 <1%
France 1 <1%
Uganda 1 <1%
Other 2 <1%
Unknown 187 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 31%
Researcher 57 27%
Student > Master 26 13%
Student > Postgraduate 8 4%
Student > Doctoral Student 7 3%
Other 26 13%
Unknown 19 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 150 72%
Biochemistry, Genetics and Molecular Biology 22 11%
Environmental Science 2 <1%
Social Sciences 2 <1%
Physics and Astronomy 2 <1%
Other 5 2%
Unknown 25 12%
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 26 June 2012.
All research outputs
#15,246,403
of 22,669,724 outputs
Outputs from BMC Genomics
#6,659
of 10,614 outputs
Outputs of similar age
#104,811
of 164,528 outputs
Outputs of similar age from BMC Genomics
#59
of 104 outputs
Altmetric has tracked 22,669,724 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 10,614 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 164,528 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.