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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
|
|---|---|
| Published in |
BMC Bioinformatics, August 2021
|
| DOI | 10.1186/s12859-021-04314-1 |
| Pubmed ID | |
| Authors |
Yang Xu, Rachel Patton McCord |
X Demographics
The data shown below were collected from the profiles of 12 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 | 5 | 42% |
| India | 1 | 8% |
| Israel | 1 | 8% |
| Sweden | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 3 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 75% |
| Members of the public | 3 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 17% |
| Researcher | 7 | 13% |
| Student > Master | 5 | 10% |
| Student > Bachelor | 4 | 8% |
| Other | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 24 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 15% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Agricultural and Biological Sciences | 4 | 8% |
| Medicine and Dentistry | 2 | 4% |
| Immunology and Microbiology | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 29 | 56% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 17 August 2021.
All research outputs
#4,612,678
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#1,716
of 7,388 outputs
Outputs of similar age
#103,128
of 431,654 outputs
Outputs of similar age from BMC Bioinformatics
#28
of 110 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,388 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 76% 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 431,654 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 110 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 74% of its contemporaries.