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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning improves the ability of sgRNA off-target propensity prediction
|
|---|---|
| Published in |
BMC Bioinformatics, February 2020
|
| DOI | 10.1186/s12859-020-3395-z |
| Pubmed ID | |
| Authors |
Qiaoyue Liu, Xiang Cheng, Gan Liu, Bohao Li, Xiuqin Liu |
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 % |
|---|---|---|
| India | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 13% |
| Student > Bachelor | 8 | 13% |
| Researcher | 7 | 11% |
| Student > Master | 4 | 7% |
| Other | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 24 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 15% |
| Computer Science | 8 | 13% |
| Medicine and Dentistry | 4 | 7% |
| Agricultural and Biological Sciences | 3 | 5% |
| Unspecified | 2 | 3% |
| Other | 13 | 21% |
| Unknown | 22 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 14 November 2020.
All research outputs
#14,709,659
of 23,859,750 outputs
Outputs from BMC Bioinformatics
#4,594
of 7,475 outputs
Outputs of similar age
#240,930
of 460,767 outputs
Outputs of similar age from BMC Bioinformatics
#71
of 135 outputs
Altmetric has tracked 23,859,750 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 35th percentile – i.e., 35% 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 460,767 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
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 is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.