You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
M2PP: a novel computational model for predicting drug-targeted pathogenic proteins
|
|---|---|
| Published in |
BMC Bioinformatics, January 2022
|
| DOI | 10.1186/s12859-021-04522-9 |
| Pubmed ID | |
| Authors |
Shiming Wang, Jie Li, Yadong Wang |
X Demographics
The data shown below were collected from the profiles of 10 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 | 3 | 30% |
| Israel | 1 | 10% |
| India | 1 | 10% |
| Sweden | 1 | 10% |
| United Kingdom | 1 | 10% |
| Unknown | 3 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 50% |
| Scientists | 5 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 1 | 20% |
| Student > Ph. D. Student | 1 | 20% |
| Student > Bachelor | 1 | 20% |
| Researcher | 1 | 20% |
| Unknown | 1 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 40% |
| Agricultural and Biological Sciences | 1 | 20% |
| Medicine and Dentistry | 1 | 20% |
| Unknown | 1 | 20% |
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 19 January 2022.
All research outputs
#8,096,303
of 24,998,746 outputs
Outputs from BMC Bioinformatics
#3,016
of 7,630 outputs
Outputs of similar age
#173,806
of 515,444 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 141 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 7,630 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 58% 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 515,444 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 65% of its contemporaries.
We're also able to compare this research output to 141 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 56% of its contemporaries.