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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrating PPI datasets with the PPI data from biomedical literature for protein complex detection
|
|---|---|
| Published in |
BMC Medical Genomics, October 2014
|
| DOI | 10.1186/1755-8794-7-s2-s3 |
| Pubmed ID | |
| Authors |
Zhi Hao Yang, Feng Ying Yu, Hong Fei Lin, Jian Wang |
| Abstract |
Protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein-protein interactions (PPIs), making it possible to predict protein complexes from protein-protein interaction networks. On the other hand, the rapidly growing biomedical literature provides a significantly large and readily available source of interaction data, which can be integrated into the protein network for better complex detection performance. |
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 % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 14% |
| Student > Bachelor | 2 | 14% |
| Student > Postgraduate | 2 | 14% |
| Student > Ph. D. Student | 1 | 7% |
| Professor | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 4 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 29% |
| Computer Science | 3 | 21% |
| Medicine and Dentistry | 2 | 14% |
| Business, Management and Accounting | 1 | 7% |
| Unknown | 4 | 29% |
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 03 November 2014.
All research outputs
#17,730,142
of 22,768,097 outputs
Outputs from BMC Medical Genomics
#790
of 1,222 outputs
Outputs of similar age
#175,306
of 260,342 outputs
Outputs of similar age from BMC Medical Genomics
#10
of 14 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,222 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% 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 260,342 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.