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Digital genotyping of sorghum – a diverse plant species with a large repeat-rich genome

Overview of attention for article published in BMC Genomics, July 2013
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Title
Digital genotyping of sorghum – a diverse plant species with a large repeat-rich genome
Published in
BMC Genomics, July 2013
DOI 10.1186/1471-2164-14-448
Pubmed ID
Authors

Daryl T Morishige, Patricia E Klein, Josie L Hilley, Sayed Mohammad Ebrahim Sahraeian, Arun Sharma, John E Mullet

Abstract

Rapid acquisition of accurate genotyping information is essential for all genetic marker-based studies. For species with relatively small genomes, complete genome resequencing is a feasible approach for genotyping; however, for species with large and highly repetitive genomes, the acquisition of whole genome sequences for the purpose of genotyping is still relatively inefficient and too expensive to be carried out on a high-throughput basis. Sorghum bicolor is a C4 grass with a sequenced genome size of ~730 Mb, of which ~80% is highly repetitive. We have developed a restriction enzyme targeted genome resequencing method for genetic analysis, termed Digital Genotyping (DG), to be applied to sorghum and other grass species with large repeat-rich genomes.

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

Geographical breakdown

Country Count As %
United States 2 3%
Netherlands 1 1%
Italy 1 1%
Thailand 1 1%
Brazil 1 1%
Japan 1 1%
Spain 1 1%
Unknown 64 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 32%
Student > Ph. D. Student 18 25%
Student > Master 8 11%
Student > Doctoral Student 7 10%
Professor > Associate Professor 4 6%
Other 7 10%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 81%
Engineering 3 4%
Chemistry 2 3%
Biochemistry, Genetics and Molecular Biology 1 1%
Environmental Science 1 1%
Other 1 1%
Unknown 6 8%
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 05 May 2015.
All research outputs
#15,708,439
of 23,340,595 outputs
Outputs from BMC Genomics
#6,777
of 10,745 outputs
Outputs of similar age
#121,882
of 195,837 outputs
Outputs of similar age from BMC Genomics
#77
of 124 outputs
Altmetric has tracked 23,340,595 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 10,745 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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We're also able to compare this research output to 124 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.