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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data
|
|---|---|
| Published in |
BMC Bioinformatics, January 2014
|
| DOI | 10.1186/1471-2105-15-28 |
| Pubmed ID | |
| Authors |
Charles Cole, Konstantinos Krampis, Konstantinos Karagiannis, Jonas S Almeida, William J Faison, Mona Motwani, Quan Wan, Anton Golikov, Yang Pan, Vahan Simonyan, Raja Mazumder |
| Abstract |
Next-generation sequencing (NGS) technologies have resulted in petabytes of scattered data, decentralized in archives, databases and sometimes in isolated hard-disks which are inaccessible for browsing and analysis. It is expected that curated secondary databases will help organize some of this Big Data thereby allowing users better navigate, search and compute on it. |
X Demographics
The data shown below were collected from the profiles of 7 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 | 3 | 43% |
| Norway | 1 | 14% |
| India | 1 | 14% |
| Sweden | 1 | 14% |
| Canada | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 57% |
| Members of the public | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| Sweden | 1 | 1% |
| Netherlands | 1 | 1% |
| Sri Lanka | 1 | 1% |
| United Kingdom | 1 | 1% |
| Unknown | 70 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 27% |
| Student > Ph. D. Student | 16 | 21% |
| Student > Bachelor | 7 | 9% |
| Other | 5 | 6% |
| Professor > Associate Professor | 5 | 6% |
| Other | 14 | 18% |
| Unknown | 9 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 29 | 38% |
| Biochemistry, Genetics and Molecular Biology | 11 | 14% |
| Computer Science | 10 | 13% |
| Medicine and Dentistry | 5 | 6% |
| Business, Management and Accounting | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 17 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 February 2014.
All research outputs
#6,026,289
of 22,741,406 outputs
Outputs from BMC Bioinformatics
#2,248
of 7,267 outputs
Outputs of similar age
#71,439
of 307,315 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 94 outputs
Altmetric has tracked 22,741,406 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,267 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 68% 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 307,315 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.