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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identifying cross-category relations in gene ontology and constructing genome-specific term association networks
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-s2-s15 |
| Pubmed ID | |
| Authors |
Jiajie Peng, Jin Chen, Yadong Wang |
| Abstract |
Gene Ontology (GO) has been widely used in biological databases, annotation projects, and computational analyses. Although the three GO categories are structured as independent ontologies, the biological relationships across the categories are not negligible for biological reasoning and knowledge integration. However, the existing cross-category ontology term similarity measures are either developed by utilizing the GO data only or based on manually curated term name similarities, ignoring the fact that GO is evolving quickly and the gene annotations are far from complete. |
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 % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 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 % |
|---|---|---|
| United Kingdom | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 41% |
| Student > Ph. D. Student | 7 | 32% |
| Professor | 1 | 5% |
| Other | 1 | 5% |
| Student > Postgraduate | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 36% |
| Biochemistry, Genetics and Molecular Biology | 6 | 27% |
| Computer Science | 2 | 9% |
| Medicine and Dentistry | 2 | 9% |
| Chemistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 3 | 14% |
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 12 March 2013.
All research outputs
#18,332,122
of 22,701,287 outputs
Outputs from BMC Bioinformatics
#6,289
of 7,254 outputs
Outputs of similar age
#216,299
of 279,318 outputs
Outputs of similar age from BMC Bioinformatics
#118
of 146 outputs
Altmetric has tracked 22,701,287 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 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 5th percentile – i.e., 5% 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 279,318 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.