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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TNER: a novel background error suppression method for mutation detection in circulating tumor DNA
|
|---|---|
| Published in |
BMC Bioinformatics, October 2018
|
| DOI | 10.1186/s12859-018-2428-3 |
| Pubmed ID | |
| Authors |
Shibing Deng, Maruja Lira, Donghui Huang, Kai Wang, Crystal Valdez, Jennifer Kinong, Paul A. Rejto, Jadwiga Bienkowska, James Hardwick, Tao Xie |
X Demographics
The data shown below were collected from the profiles of 4 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 Kingdom | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
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 % |
|---|---|---|
| Unknown | 74 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 24% |
| Student > Ph. D. Student | 10 | 14% |
| Student > Bachelor | 7 | 9% |
| Other | 4 | 5% |
| Student > Master | 3 | 4% |
| Other | 5 | 7% |
| Unknown | 27 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 26% |
| Agricultural and Biological Sciences | 11 | 15% |
| Medicine and Dentistry | 7 | 9% |
| Engineering | 2 | 3% |
| Computer Science | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 30 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 30 June 2023.
All research outputs
#3,972,013
of 24,682,395 outputs
Outputs from BMC Bioinformatics
#1,347
of 7,567 outputs
Outputs of similar age
#74,779
of 355,134 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 135 outputs
Altmetric has tracked 24,682,395 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,567 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 82% 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 355,134 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 78% of its contemporaries.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.