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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A rule-based ontological framework for the classification of molecules
|
|---|---|
| Published in |
Journal of Biomedical Semantics, April 2014
|
| DOI | 10.1186/2041-1480-5-17 |
| Pubmed ID | |
| Authors |
Despoina Magka, Markus Krötzsch, Ian Horrocks |
| Abstract |
A variety of key activities within life sciences research involves integrating and intelligently managing large amounts of biochemical information. Semantic technologies provide an intuitive way to organise and sift through these rapidly growing datasets via the design and maintenance of ontology-supported knowledge bases. To this end, OWL---a W3C standard declarative language--- has been extensively used in the deployment of biochemical ontologies that can be conveniently organised using the classification facilities of OWL-based tools. One of the most established ontologies for the chemical domain is ChEBI, an open-access dictionary of molecular entities that supplies high quality annotation and taxonomical information for biologically relevant compounds. However, ChEBI is being manually expanded which hinders its potential to grow due to the limited availability of human resources. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 3% |
| Unknown | 29 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 20% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Master | 4 | 13% |
| Lecturer > Senior Lecturer | 2 | 7% |
| Student > Postgraduate | 2 | 7% |
| Other | 6 | 20% |
| Unknown | 5 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 30% |
| Agricultural and Biological Sciences | 5 | 17% |
| Engineering | 4 | 13% |
| Chemistry | 2 | 7% |
| Arts and Humanities | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 6 | 20% |
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 21 January 2015.
All research outputs
#14,599,900
of 25,373,627 outputs
Outputs from Journal of Biomedical Semantics
#183
of 368 outputs
Outputs of similar age
#116,305
of 239,868 outputs
Outputs of similar age from Journal of Biomedical Semantics
#3
of 8 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 48th percentile – i.e., 48% 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 239,868 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 50% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.