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 |
Detecting protein complexes in protein interaction networks using a ranking algorithm with a refined merging procedure
|
|---|---|
| Published in |
BMC Bioinformatics, June 2014
|
| DOI | 10.1186/1471-2105-15-204 |
| Pubmed ID | |
| Authors |
Eileen Marie Hanna, Nazar Zaki |
| Abstract |
Developing suitable methods for the identification of protein complexes remains an active research area. It is important since it allows better understanding of cellular functions as well as malfunctions and it consequently leads to producing more effective cures for diseases. In this context, various computational approaches were introduced to complement high-throughput experimental methods which typically involve large datasets, are expensive in terms of time and cost, and are usually subject to spurious interactions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 25% |
| Researcher | 4 | 17% |
| Student > Master | 4 | 17% |
| Professor | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 4 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 54% |
| Agricultural and Biological Sciences | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Medicine and Dentistry | 1 | 4% |
| Neuroscience | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 4 | 17% |
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 19 June 2014.
All research outputs
#20,940,593
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#7,009
of 7,418 outputs
Outputs of similar age
#194,681
of 229,942 outputs
Outputs of similar age from BMC Bioinformatics
#144
of 155 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 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 1st percentile – i.e., 1% 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 229,942 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.