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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditions
|
|---|---|
| Published in |
Journal of Translational Medicine, April 2014
|
| DOI | 10.1186/1479-5876-12-99 |
| Pubmed ID | |
| Authors |
Hyojung Paik, Hyoung-Sam Heo, Hyo-jeong Ban, Seong Beom Cho |
| Abstract |
Human diseases frequently cause complications such as obesity-induced diabetes and share numbers of pathological conditions, such as inflammation, by dysfunctions of common functional modules, such as protein-protein interactions (PPIs). |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Unknown | 44 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 24% |
| Researcher | 11 | 24% |
| Student > Master | 9 | 20% |
| Student > Postgraduate | 2 | 4% |
| Professor | 2 | 4% |
| Other | 4 | 9% |
| Unknown | 6 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 36% |
| Agricultural and Biological Sciences | 13 | 29% |
| Computer Science | 4 | 9% |
| Unspecified | 1 | 2% |
| Mathematics | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 7 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 13 June 2014.
All research outputs
#12,704,903
of 22,753,345 outputs
Outputs from Journal of Translational Medicine
#1,426
of 3,977 outputs
Outputs of similar age
#104,617
of 226,967 outputs
Outputs of similar age from Journal of Translational Medicine
#18
of 66 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,977 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 63% 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 226,967 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 53% of its contemporaries.
We're also able to compare this research output to 66 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 71% of its contemporaries.