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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions
|
|---|---|
| Published in |
Journal of Biomedical Semantics, January 2015
|
| DOI | 10.1186/2041-1480-6-2 |
| Pubmed ID | |
| Authors |
Junguk Hur, Arzucan Özgür, Zuoshuang Xiang, Yongqun He |
| Abstract |
Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. |
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 % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Turkey | 1 | 5% |
| United States | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 18% |
| Student > Bachelor | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Ph. D. Student | 2 | 9% |
| Student > Doctoral Student | 1 | 5% |
| Other | 4 | 18% |
| Unknown | 5 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 27% |
| Agricultural and Biological Sciences | 5 | 23% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Engineering | 2 | 9% |
| Neuroscience | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 16 February 2020.
All research outputs
#2,243,357
of 22,789,076 outputs
Outputs from Journal of Biomedical Semantics
#32
of 364 outputs
Outputs of similar age
#33,351
of 352,380 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 12 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 91% 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 352,380 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.