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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DeepSV: accurate calling of genomic deletions from high-throughput sequencing data using deep convolutional neural network
|
|---|---|
| Published in |
BMC Bioinformatics, December 2019
|
| DOI | 10.1186/s12859-019-3299-y |
| Pubmed ID | |
| Authors |
Lei Cai, Yufeng Wu, Jingyang Gao |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 15 | 18% |
| Researcher | 14 | 16% |
| Student > Ph. D. Student | 11 | 13% |
| Student > Doctoral Student | 6 | 7% |
| Student > Bachelor | 5 | 6% |
| Other | 5 | 6% |
| Unknown | 29 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 21 | 25% |
| Computer Science | 13 | 15% |
| Agricultural and Biological Sciences | 11 | 13% |
| Medicine and Dentistry | 4 | 5% |
| Engineering | 2 | 2% |
| Other | 1 | 1% |
| Unknown | 33 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 02 February 2022.
All research outputs
#6,982,354
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#2,645
of 7,387 outputs
Outputs of similar age
#149,070
of 460,737 outputs
Outputs of similar age from BMC Bioinformatics
#77
of 228 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,387 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 gotten more attention than average, scoring higher than 63% 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 460,737 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 228 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.