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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures
|
|---|---|
| Published in |
BMC Bioinformatics, September 2013
|
| DOI | 10.1186/1471-2105-14-284 |
| Pubmed ID | |
| Authors |
Gaston K Mazandu, Nicola J Mulder |
| Abstract |
The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. |
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 % |
|---|---|---|
| Japan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 2% |
| France | 1 | 2% |
| Brazil | 1 | 2% |
| United Kingdom | 1 | 2% |
| Poland | 1 | 2% |
| Unknown | 46 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 37% |
| Student > Master | 9 | 18% |
| Student > Ph. D. Student | 8 | 16% |
| Student > Bachelor | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 35% |
| Computer Science | 12 | 24% |
| Biochemistry, Genetics and Molecular Biology | 10 | 20% |
| Medicine and Dentistry | 2 | 4% |
| Neuroscience | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 5 | 10% |
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 30 September 2013.
All research outputs
#15,280,625
of 22,723,682 outputs
Outputs from BMC Bioinformatics
#5,367
of 7,262 outputs
Outputs of similar age
#124,770
of 203,246 outputs
Outputs of similar age from BMC Bioinformatics
#67
of 102 outputs
Altmetric has tracked 22,723,682 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,262 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 18th percentile – i.e., 18% 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 203,246 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 102 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.