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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GeDi: applying suffix arrays to increase the repertoire of detectable SNVs in tumour genomes
|
|---|---|
| Published in |
BMC Bioinformatics, February 2020
|
| DOI | 10.1186/s12859-020-3367-3 |
| Pubmed ID | |
| Authors |
Izaak Coleman, Giacomo Corleone, James Arram, Ho-Cheung Ng, Luca Magnani, Wayne Luk |
X Demographics
The data shown below were collected from the profiles of 3 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 | 2 | 67% |
| India | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 38% |
| Student > Master | 2 | 25% |
| Researcher | 1 | 13% |
| Student > Bachelor | 1 | 13% |
| Unknown | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 25% |
| Agricultural and Biological Sciences | 1 | 13% |
| Biochemistry, Genetics and Molecular Biology | 1 | 13% |
| Medicine and Dentistry | 1 | 13% |
| Engineering | 1 | 13% |
| Other | 0 | 0% |
| Unknown | 2 | 25% |
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 07 February 2020.
All research outputs
#15,598,026
of 23,191,112 outputs
Outputs from BMC Bioinformatics
#5,438
of 7,345 outputs
Outputs of similar age
#269,328
of 449,685 outputs
Outputs of similar age from BMC Bioinformatics
#103
of 169 outputs
Altmetric has tracked 23,191,112 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,345 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 449,685 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.