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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data
|
|---|---|
| Published in |
BioData Mining, January 2022
|
| DOI | 10.1186/s13040-021-00285-4 |
| Pubmed ID | |
| Authors |
Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquin Dopazo, Isabel Nepomuceno |
X Demographics
The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 5 | 29% |
| Italy | 2 | 12% |
| Austria | 1 | 6% |
| France | 1 | 6% |
| Singapore | 1 | 6% |
| Unknown | 7 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 53% |
| Scientists | 7 | 41% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 22% |
| Student > Ph. D. Student | 5 | 14% |
| Unspecified | 3 | 8% |
| Other | 3 | 8% |
| Student > Master | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 13 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 17% |
| Computer Science | 5 | 14% |
| Unspecified | 3 | 8% |
| Agricultural and Biological Sciences | 3 | 8% |
| Medicine and Dentistry | 2 | 6% |
| Other | 3 | 8% |
| Unknown | 14 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 10 January 2022.
All research outputs
#3,365,474
of 24,387,992 outputs
Outputs from BioData Mining
#65
of 316 outputs
Outputs of similar age
#80,422
of 509,931 outputs
Outputs of similar age from BioData Mining
#2
of 6 outputs
Altmetric has tracked 24,387,992 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 316 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 79% 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 509,931 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 84% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.