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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TMbed: transmembrane proteins predicted through language model embeddings
|
|---|---|
| Published in |
BMC Bioinformatics, August 2022
|
| DOI | 10.1186/s12859-022-04873-x |
| Pubmed ID | |
| Authors |
Michael Bernhofer, Burkhard Rost |
X Demographics
The data shown below were collected from the profiles of 9 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 | 22% |
| Japan | 1 | 11% |
| Sweden | 1 | 11% |
| India | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
| Members of the public | 1 | 11% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 17% |
| Researcher | 7 | 17% |
| Student > Bachelor | 4 | 10% |
| Lecturer | 3 | 7% |
| Student > Master | 3 | 7% |
| Other | 5 | 12% |
| Unknown | 12 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 14 | 34% |
| Computer Science | 4 | 10% |
| Agricultural and Biological Sciences | 3 | 7% |
| Unspecified | 2 | 5% |
| Chemical Engineering | 1 | 2% |
| Other | 5 | 12% |
| Unknown | 12 | 29% |
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 29 September 2022.
All research outputs
#7,174,980
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#2,657
of 7,454 outputs
Outputs of similar age
#131,476
of 434,564 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 134 outputs
Altmetric has tracked 23,881,329 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 7,454 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 434,564 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 69% of its contemporaries.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.