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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, January 2013
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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2 tweeters

Citations

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46 Dimensions

Readers on

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62 Mendeley

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Summary Twitter Dimensions citations
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Title
Digital genotyping of sorghum -- a diverse plant species with a large repeat-rich genome
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-448
Pubmed ID
23829350
Authors

Daryl T Morishige, Patricia E Klein, Josie L Hilley, Sayed Mohammad 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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Twitter Demographics

The data shown below were collected from the profiles of 2 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Thailand 1 2%
Brazil 1 2%
Italy 1 2%
Spain 1 2%
Japan 1 2%
Netherlands 1 2%
Unknown 54 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 34%
Student > Ph. D. Student 17 27%
Student > Master 7 11%
Student > Doctoral Student 5 8%
Professor > Associate Professor 4 6%
Other 5 8%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 81%
Engineering 3 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Computer Science 1 2%
Chemistry 1 2%
Other 1 2%
Unknown 5 8%

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 05 May 2015.
All research outputs
#2,319,822
of 5,060,128 outputs
Outputs from BMC Genomics
#2,403
of 4,605 outputs
Outputs of similar age
#38,653
of 93,953 outputs
Outputs of similar age from BMC Genomics
#82
of 153 outputs
Altmetric has tracked 5,060,128 research outputs across all sources so far. This one has received more attention than most of these and is in the 51st percentile.
So far Altmetric has tracked 4,605 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 42nd percentile – i.e., 42% 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 93,953 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 55% of its contemporaries.
We're also able to compare this research output to 153 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.

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