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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 3% |
| United States | 1 | 2% |
| Sweden | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 56 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 25% |
| Researcher | 12 | 20% |
| Student > Master | 10 | 16% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 5 | 8% |
| Other | 9 | 15% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 41% |
| Biochemistry, Genetics and Molecular Biology | 20 | 33% |
| Computer Science | 4 | 7% |
| Medicine and Dentistry | 4 | 7% |
| Chemistry | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 7 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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
#18,972,324
of 23,520,142 outputs
Outputs from BMC Genomics
#8,314
of 10,787 outputs
Outputs of similar age
#130,952
of 170,353 outputs
Outputs of similar age from BMC Genomics
#88
of 113 outputs
Altmetric has tracked 23,520,142 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,787 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 170,353 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.