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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MAE-FMD: Multi-agent evolutionary method for functional module detection in protein-protein interaction networks
|
|---|---|
| Published in |
BMC Bioinformatics, September 2014
|
| DOI | 10.1186/1471-2105-15-325 |
| Pubmed ID | |
| Authors |
Jun Zhong Ji, Lang Jiao, Cui Cui Yang, Jia Wei Lv, Ai Dong Zhang |
| Abstract |
Studies of functional modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approaches have played an important role in detecting functional modules. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 38% |
| Researcher | 4 | 31% |
| Student > Master | 3 | 23% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 46% |
| Agricultural and Biological Sciences | 3 | 23% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Immunology and Microbiology | 1 | 8% |
| Design | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 01 October 2014.
All research outputs
#18,379,018
of 22,764,165 outputs
Outputs from BMC Bioinformatics
#6,307
of 7,273 outputs
Outputs of similar age
#180,445
of 252,706 outputs
Outputs of similar age from BMC Bioinformatics
#86
of 107 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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 252,706 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.