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Whole genome sequencing of peach (Prunus persica L.) for SNP identification and selection

Overview of attention for article published in BMC Genomics, November 2011
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
4 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
68 Dimensions

Readers on

mendeley
147 Mendeley
citeulike
2 CiteULike
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Title
Whole genome sequencing of peach (Prunus persica L.) for SNP identification and selection
Published in
BMC Genomics, November 2011
DOI 10.1186/1471-2164-12-569
Pubmed ID
Authors

Riaz Ahmad, Dan E Parfitt, Joseph Fass, Ebenezer Ogundiwin, Amit Dhingra, Thomas M Gradziel, Dawei Lin, Nikhil A Joshi, Pedro J Martinez-Garcia, Carlos H Crisosto

Abstract

The application of next generation sequencing technologies and bioinformatic scripts to identify high frequency SNPs distributed throughout the peach genome is described. Three peach genomes were sequenced using Roche 454 and Illumina/Solexa technologies to obtain long contigs for alignment to the draft 'Lovell' peach sequence as well as sufficient depth of coverage for 'in silico' SNP discovery.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 1%
Netherlands 1 <1%
Norway 1 <1%
Brazil 1 <1%
Israel 1 <1%
Czechia 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Mexico 1 <1%
Other 2 1%
Unknown 135 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 31%
Student > Ph. D. Student 33 22%
Student > Master 17 12%
Professor > Associate Professor 13 9%
Student > Bachelor 7 5%
Other 20 14%
Unknown 12 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 101 69%
Biochemistry, Genetics and Molecular Biology 19 13%
Environmental Science 3 2%
Computer Science 2 1%
Earth and Planetary Sciences 2 1%
Other 8 5%
Unknown 12 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 November 2016.
All research outputs
#6,328,154
of 12,373,620 outputs
Outputs from BMC Genomics
#2,920
of 7,296 outputs
Outputs of similar age
#85,512
of 217,084 outputs
Outputs of similar age from BMC Genomics
#245
of 554 outputs
Altmetric has tracked 12,373,620 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,296 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 217,084 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 60% of its contemporaries.
We're also able to compare this research output to 554 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.