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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Rough Guide to In Silico Function Prediction, or How To Use Sequence and Structure Information To Predict Protein Function
|
|---|---|
| Published in |
PLoS Computational Biology, October 2008
|
| DOI | 10.1371/journal.pcbi.1000160 |
| Pubmed ID | |
| Authors |
Marco Punta, Yanay Ofran |
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 % |
|---|---|---|
| United States | 4 | 24% |
| Canada | 2 | 12% |
| United Kingdom | 2 | 12% |
| France | 1 | 6% |
| Netherlands | 1 | 6% |
| Colombia | 1 | 6% |
| Unknown | 6 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 59% |
| Scientists | 6 | 35% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 366 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 13 | 4% |
| United States | 9 | 2% |
| Germany | 5 | 1% |
| Brazil | 5 | 1% |
| Australia | 4 | 1% |
| France | 3 | <1% |
| Denmark | 3 | <1% |
| Japan | 2 | <1% |
| Mexico | 2 | <1% |
| Other | 15 | 4% |
| Unknown | 305 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 97 | 27% |
| Researcher | 96 | 26% |
| Student > Master | 44 | 12% |
| Student > Bachelor | 30 | 8% |
| Professor > Associate Professor | 15 | 4% |
| Other | 60 | 16% |
| Unknown | 24 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 176 | 48% |
| Biochemistry, Genetics and Molecular Biology | 66 | 18% |
| Computer Science | 41 | 11% |
| Chemistry | 14 | 4% |
| Immunology and Microbiology | 7 | 2% |
| Other | 31 | 8% |
| Unknown | 31 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 19 October 2018.
All research outputs
#4,158,501
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#3,403
of 8,960 outputs
Outputs of similar age
#16,046
of 104,773 outputs
Outputs of similar age from PLoS Computational Biology
#13
of 48 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 61% 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 104,773 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 48 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 72% of its contemporaries.