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Separating homeologs by phasing in the tetraploid wheat transcriptome

Overview of attention for article published in Genome Biology, June 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog
twitter
33 X users
patent
2 patents

Citations

dimensions_citation
125 Dimensions

Readers on

mendeley
248 Mendeley
citeulike
3 CiteULike
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Title
Separating homeologs by phasing in the tetraploid wheat transcriptome
Published in
Genome Biology, June 2013
DOI 10.1186/gb-2013-14-6-r66
Pubmed ID
Authors

Ksenia V Krasileva, Vince Buffalo, Paul Bailey, Stephen Pearce, Sarah Ayling, Facundo Tabbita, Marcelo Soria, Shichen Wang, IWGS Consortium, Eduard Akhunov, Cristobal Uauy, Jorge Dubcovsky

Abstract

The high level of identity among duplicated homoeologous genomes in tetraploid pasta wheat presents substantial challenges for de novo transcriptome assembly. To solve this problem, we develop a specialized bioinformatics workflow that optimizes transcriptome assembly and separation of merged homoeologs. To evaluate our strategy, we sequence and assemble the transcriptome of one of the diploid ancestors of pasta wheat, and compare both assemblies with a benchmark set of 13,472 full-length, non-redundant bread wheat cDNAs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 33 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 248 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 6 2%
United States 3 1%
Italy 2 <1%
Germany 2 <1%
Argentina 2 <1%
Sweden 2 <1%
Austria 1 <1%
Australia 1 <1%
Brazil 1 <1%
Other 5 2%
Unknown 223 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 26%
Researcher 60 24%
Student > Master 21 8%
Student > Bachelor 17 7%
Student > Doctoral Student 15 6%
Other 51 21%
Unknown 20 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 174 70%
Biochemistry, Genetics and Molecular Biology 33 13%
Computer Science 11 4%
Engineering 3 1%
Materials Science 2 <1%
Other 2 <1%
Unknown 23 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 30 November 2022.
All research outputs
#1,230,158
of 25,374,917 outputs
Outputs from Genome Biology
#929
of 4,467 outputs
Outputs of similar age
#10,177
of 208,950 outputs
Outputs of similar age from Genome Biology
#12
of 66 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 79% 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 208,950 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.