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A pipeline for the de novo assembly of the Themira biloba(Sepsidae: Diptera) transcriptome using a multiple k-mer length approach

Overview of attention for article published in BMC Genomics, March 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

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4 X users
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1 Facebook page

Citations

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14 Dimensions

Readers on

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79 Mendeley
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2 CiteULike
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Title
A pipeline for the de novo assembly of the Themira biloba(Sepsidae: Diptera) transcriptome using a multiple k-mer length approach
Published in
BMC Genomics, March 2014
DOI 10.1186/1471-2164-15-188
Pubmed ID
Authors

Dacotah Melicher, Alex S Torson, Ian Dworkin, Julia H Bowsher

Abstract

The Sepsidae family of flies is a model for investigating how sexual selection shapes courtship and sexual dimorphism in a comparative framework. However, like many non-model systems, there are few molecular resources available. Large-scale sequencing and assembly have not been performed in any sepsid, and the lack of a closely related genome makes investigation of gene expression challenging. Our goal was to develop an automated pipeline for de novo transcriptome assembly, and to use that pipeline to assemble and analyze the transcriptome of the sepsid Themira biloba.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 3 4%
United Kingdom 2 3%
United States 2 3%
Spain 2 3%
Brazil 1 1%
Portugal 1 1%
France 1 1%
Vietnam 1 1%
Unknown 66 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 32%
Researcher 18 23%
Student > Master 10 13%
Other 5 6%
Student > Bachelor 5 6%
Other 9 11%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 56%
Biochemistry, Genetics and Molecular Biology 10 13%
Computer Science 6 8%
Medicine and Dentistry 4 5%
Social Sciences 1 1%
Other 3 4%
Unknown 11 14%
Attention Score in Context

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 23 September 2014.
All research outputs
#14,387,928
of 25,374,647 outputs
Outputs from BMC Genomics
#4,750
of 11,244 outputs
Outputs of similar age
#113,225
of 235,693 outputs
Outputs of similar age from BMC Genomics
#81
of 206 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 56% 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 235,693 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 51% of its contemporaries.
We're also able to compare this research output to 206 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 59% of its contemporaries.