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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Large language models generate functional protein sequences across diverse families
|
|---|---|
| Published in |
Nature Biotechnology, January 2023
|
| DOI | 10.1038/s41587-022-01618-2 |
| Pubmed ID | |
| Authors |
Ali Madani, Ben Krause, Eric R. Greene, Subu Subramanian, Benjamin P. Mohr, James M. Holton, Jose Luis Olmos, Caiming Xiong, Zachary Z. Sun, Richard Socher, James S. Fraser, Nikhil Naik |
X Demographics
The data shown below were collected from the profiles of 1,160 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 | 224 | 19% |
| United Kingdom | 49 | 4% |
| Japan | 33 | 3% |
| Canada | 22 | 2% |
| Germany | 21 | 2% |
| India | 20 | 2% |
| France | 16 | 1% |
| Australia | 16 | 1% |
| Italy | 13 | 1% |
| Other | 188 | 16% |
| Unknown | 558 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 775 | 67% |
| Scientists | 355 | 31% |
| Practitioners (doctors, other healthcare professionals) | 16 | 1% |
| Science communicators (journalists, bloggers, editors) | 13 | 1% |
| Unknown | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 537 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 537 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 93 | 17% |
| Researcher | 90 | 17% |
| Student > Bachelor | 31 | 6% |
| Student > Master | 30 | 6% |
| Other | 27 | 5% |
| Other | 70 | 13% |
| Unknown | 196 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 125 | 23% |
| Computer Science | 51 | 9% |
| Agricultural and Biological Sciences | 49 | 9% |
| Chemistry | 22 | 4% |
| Engineering | 14 | 3% |
| Other | 70 | 13% |
| Unknown | 206 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1096. 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 22 April 2024.
All research outputs
#14,154
of 25,816,430 outputs
Outputs from Nature Biotechnology
#27
of 8,627 outputs
Outputs of similar age
#430
of 478,075 outputs
Outputs of similar age from Nature Biotechnology
#1
of 119 outputs
Altmetric has tracked 25,816,430 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,627 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.6. This one has done particularly well, scoring higher than 99% 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 478,075 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.