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Detecting transcription of ribosomal protein pseudogenes in diverse human tissues from RNA-seq data

Overview of attention for article published in BMC Genomics, August 2012
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Mentioned by

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2 tweeters

Citations

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25 Dimensions

Readers on

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55 Mendeley
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2 CiteULike
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Title
Detecting transcription of ribosomal protein pseudogenes in diverse human tissues from RNA-seq data
Published in
BMC Genomics, August 2012
DOI 10.1186/1471-2164-13-412
Pubmed ID
Authors

Peter Tonner, Vinodh Srinivasasainagendra, Shaojie Zhang, Degui Zhi

Abstract

Ribosomal proteins (RPs) have about 2000 pseudogenes in the human genome. While anecdotal reports for RP pseudogene transcription exists, it is unclear to what extent these pseudogenes are transcribed. The RP pseudogene transcription is difficult to identify in microarrays due to potential cross-hybridization between transcripts from the parent genes and pseudogenes. Recently, transcriptome sequencing (RNA-seq) provides an opportunity to ascertain the transcription of pseudogenes. A challenge for pseudogene expression discovery in RNA-seq data lies in the difficulty to uniquely identify reads mapped to pseudogene regions, which are typically also similar to the parent genes.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 4%
Sweden 1 2%
United States 1 2%
Australia 1 2%
Unknown 50 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 27%
Researcher 12 22%
Student > Master 10 18%
Student > Doctoral Student 4 7%
Student > Postgraduate 3 5%
Other 8 15%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 42%
Biochemistry, Genetics and Molecular Biology 19 35%
Medicine and Dentistry 4 7%
Computer Science 3 5%
Chemistry 1 2%
Other 0 0%
Unknown 5 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 August 2012.
All research outputs
#7,731,594
of 12,373,620 outputs
Outputs from BMC Genomics
#4,616
of 7,313 outputs
Outputs of similar age
#69,981
of 125,367 outputs
Outputs of similar age from BMC Genomics
#2
of 3 outputs
Altmetric has tracked 12,373,620 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,313 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 36th percentile – i.e., 36% 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 125,367 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.