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X Demographics
Mendeley readers
Attention Score in Context
| Title |
New concepts for building vocabulary for cell image ontologies
|
|---|---|
| Published in |
BMC Bioinformatics, December 2011
|
| DOI | 10.1186/1471-2105-12-487 |
| Pubmed ID | |
| Authors |
Anne L Plant, John T Elliott, Talapady N Bhat |
| Abstract |
There are significant challenges associated with the building of ontologies for cell biology experiments including the large numbers of terms and their synonyms. These challenges make it difficult to simultaneously query data from multiple experiments or ontologies. If vocabulary terms were consistently used and reused across and within ontologies, queries would be possible through shared terms. One approach to achieving this is to strictly control the terms used in ontologies in the form of a pre-defined schema, but this approach limits the individual researcher's ability to create new terms when needed to describe new experiments. |
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 % |
|---|---|---|
| Unknown | 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 6% |
| Netherlands | 1 | 3% |
| Peru | 1 | 3% |
| Mexico | 1 | 3% |
| Russia | 1 | 3% |
| Unknown | 27 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 33% |
| Student > Ph. D. Student | 7 | 21% |
| Professor | 3 | 9% |
| Librarian | 2 | 6% |
| Lecturer | 2 | 6% |
| Other | 7 | 21% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 27% |
| Agricultural and Biological Sciences | 7 | 21% |
| Linguistics | 4 | 12% |
| Chemistry | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 7 | 21% |
| Unknown | 2 | 6% |
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 22 November 2012.
All research outputs
#18,321,703
of 22,687,320 outputs
Outputs from BMC Bioinformatics
#6,287
of 7,252 outputs
Outputs of similar age
#195,539
of 243,118 outputs
Outputs of similar age from BMC Bioinformatics
#83
of 100 outputs
Altmetric has tracked 22,687,320 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 7,252 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 243,118 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.