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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detecting temporal protein complexes from dynamic protein-protein interaction networks
|
|---|---|
| Published in |
BMC Bioinformatics, October 2014
|
| DOI | 10.1186/1471-2105-15-335 |
| Pubmed ID | |
| Authors |
Le Ou-Yang, Dao-Qing Dai, Xiao-Li Li, Min Wu, Xiao-Fei Zhang, Peng Yang |
| Abstract |
Proteins dynamically interact with each other to perform their biological functions. The dynamic operations of protein interaction networks (PPI) are also reflected in the dynamic formations of protein complexes. Existing protein complex detection algorithms usually overlook the inherent temporal nature of protein interactions within PPI networks. Systematically analyzing the temporal protein complexes can not only improve the accuracy of protein complex detection, but also strengthen our biological knowledge on the dynamic protein assembly processes for cellular organization. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 42 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 30% |
| Researcher | 8 | 18% |
| Student > Master | 7 | 16% |
| Student > Bachelor | 3 | 7% |
| Student > Postgraduate | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 25% |
| Agricultural and Biological Sciences | 8 | 18% |
| Biochemistry, Genetics and Molecular Biology | 7 | 16% |
| Mathematics | 2 | 5% |
| Physics and Astronomy | 2 | 5% |
| Other | 5 | 11% |
| Unknown | 9 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 06 October 2014.
All research outputs
#14,786,597
of 22,765,347 outputs
Outputs from BMC Bioinformatics
#5,040
of 7,273 outputs
Outputs of similar age
#140,137
of 254,034 outputs
Outputs of similar age from BMC Bioinformatics
#68
of 109 outputs
Altmetric has tracked 22,765,347 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% 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 26th percentile – i.e., 26% 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 254,034 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.