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Development and application of a 6.5 million feature Affymetrix Genechip® for massively parallel discovery of single position polymorphisms in lettuce (Lactuca spp.)

Overview of attention for article published in BMC Genomics, May 2012
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1 X user

Citations

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53 Mendeley
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Title
Development and application of a 6.5 million feature Affymetrix Genechip® for massively parallel discovery of single position polymorphisms in lettuce (Lactuca spp.)
Published in
BMC Genomics, May 2012
DOI 10.1186/1471-2164-13-185
Pubmed ID
Authors

Kevin Stoffel, Hans van Leeuwen, Alexander Kozik, David Caldwell, Hamid Ashrafi, Xinping Cui, Xiaoping Tan, Theresa Hill, Sebastian Reyes-Chin-Wo, Maria-Jose Truco, Richard W Michelmore, Allen Van Deynze

Abstract

High-resolution genetic maps are needed in many crops to help characterize the genetic diversity that determines agriculturally important traits. Hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. However, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce (Lactuca sativa).

X Demographics

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

Geographical breakdown

Country Count As %
Netherlands 2 4%
Unknown 51 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 26%
Student > Ph. D. Student 12 23%
Student > Master 7 13%
Student > Doctoral Student 5 9%
Student > Postgraduate 3 6%
Other 7 13%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 70%
Biochemistry, Genetics and Molecular Biology 2 4%
Medicine and Dentistry 2 4%
Chemistry 2 4%
Business, Management and Accounting 1 2%
Other 3 6%
Unknown 6 11%
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 15 May 2012.
All research outputs
#18,587,406
of 23,023,224 outputs
Outputs from BMC Genomics
#8,229
of 10,699 outputs
Outputs of similar age
#127,172
of 164,706 outputs
Outputs of similar age from BMC Genomics
#63
of 85 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,699 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 164,706 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.