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How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?

Overview of attention for article published in BMC Genomics, December 2012
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

blogs
3 blogs
twitter
22 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user
f1000
1 research highlight platform

Citations

dimensions_citation
179 Dimensions

Readers on

mendeley
825 Mendeley
citeulike
5 CiteULike
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Title
How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?
Published in
BMC Genomics, December 2012
DOI 10.1186/1471-2164-13-734
Pubmed ID
Authors

Brian J Haas, Melissa Chin, Chad Nusbaum, Bruce W Birren, Jonathan Livny

Abstract

High-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance.

Twitter Demographics

The data shown below were collected from the profiles of 22 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 825 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 17 2%
Germany 5 <1%
United Kingdom 5 <1%
Canada 4 <1%
Netherlands 2 <1%
France 2 <1%
Brazil 2 <1%
Australia 2 <1%
Sweden 2 <1%
Other 25 3%
Unknown 759 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 238 29%
Researcher 194 24%
Student > Master 104 13%
Student > Bachelor 50 6%
Student > Postgraduate 39 5%
Other 151 18%
Unknown 49 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 444 54%
Biochemistry, Genetics and Molecular Biology 157 19%
Immunology and Microbiology 47 6%
Environmental Science 28 3%
Engineering 25 3%
Other 60 7%
Unknown 64 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 35. 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 02 February 2021.
All research outputs
#826,438
of 20,194,585 outputs
Outputs from BMC Genomics
#138
of 9,957 outputs
Outputs of similar age
#8,858
of 283,932 outputs
Outputs of similar age from BMC Genomics
#8
of 659 outputs
Altmetric has tracked 20,194,585 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 9,957 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 98% 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 283,932 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 96% of its contemporaries.
We're also able to compare this research output to 659 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.