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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Whole human genome proteogenomic mapping for ENCODE cell line data: identifying protein-coding regions
|
|---|---|
| Published in |
BMC Genomics, February 2013
|
| DOI | 10.1186/1471-2164-14-141 |
| Pubmed ID | |
| Authors |
Jainab Khatun, Yanbao Yu, John A Wrobel, Brian A Risk, Harsha P Gunawardena, Ashley Secrest, Wendy J Spitzer, Ling Xie, Li Wang, Xian Chen, Morgan C Giddings |
| Abstract |
Proteogenomic mapping is an approach that uses mass spectrometry data from proteins to directly map protein-coding genes and could aid in locating translational regions in the human genome. In concert with the ENcyclopedia of DNA Elements (ENCODE) project, we applied proteogenomic mapping to produce proteogenomic tracks for the UCSC Genome Browser, to explore which putative translational regions may be missing from the human genome. |
X Demographics
The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 39% |
| United Kingdom | 4 | 22% |
| France | 1 | 6% |
| Unknown | 6 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 44% |
| Members of the public | 7 | 39% |
| Practitioners (doctors, other healthcare professionals) | 2 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 3% |
| United States | 1 | 1% |
| Turkey | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 69 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 24 | 32% |
| Student > Ph. D. Student | 16 | 22% |
| Student > Master | 9 | 12% |
| Professor > Associate Professor | 4 | 5% |
| Student > Bachelor | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 7 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 27 | 36% |
| Biochemistry, Genetics and Molecular Biology | 23 | 31% |
| Medicine and Dentistry | 6 | 8% |
| Chemistry | 4 | 5% |
| Immunology and Microbiology | 2 | 3% |
| Other | 4 | 5% |
| Unknown | 8 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 18 November 2013.
All research outputs
#2,558,449
of 25,374,917 outputs
Outputs from BMC Genomics
#702
of 11,244 outputs
Outputs of similar age
#20,395
of 205,219 outputs
Outputs of similar age from BMC Genomics
#13
of 194 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 93% 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 205,219 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 90% of its contemporaries.
We're also able to compare this research output to 194 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 93% of its contemporaries.