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Mendeley readers
Attention Score in Context
| Title |
Ontology of physics for biology: representing physical dependencies as a basis for biological processes
|
|---|---|
| Published in |
Journal of Biomedical Semantics, December 2013
|
| DOI | 10.1186/2041-1480-4-41 |
| Pubmed ID | |
| Authors |
Daniel L Cook, Maxwell L Neal, Fred L Bookstein, John H Gennari |
| Abstract |
In prior work, we presented the Ontology of Physics for Biology (OPB) as a computational ontology for use in the annotation and representations of biophysical knowledge encoded in repositories of physics-based biosimulation models. We introduced OPB:Physical entity and OPB:Physical property classes that extend available spatiotemporal representations of physical entities and processes to explicitly represent the thermodynamics and dynamics of physiological processes. Our utilitarian, long-term aim is to develop computational tools for creating and querying formalized physiological knowledge for use by multiscale "physiome" projects such as the EU's Virtual Physiological Human (VPH) and NIH's Virtual Physiological Rat (VPR). |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 7% |
| Mexico | 1 | 3% |
| United Kingdom | 1 | 3% |
| Unknown | 25 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 21% |
| Researcher | 5 | 17% |
| Professor > Associate Professor | 4 | 14% |
| Student > Bachelor | 4 | 14% |
| Professor | 3 | 10% |
| Other | 3 | 10% |
| Unknown | 4 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 28% |
| Computer Science | 6 | 21% |
| Biochemistry, Genetics and Molecular Biology | 5 | 17% |
| Engineering | 4 | 14% |
| Arts and Humanities | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 3 | 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 19 December 2013.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Journal of Biomedical Semantics
#240
of 368 outputs
Outputs of similar age
#205,392
of 320,940 outputs
Outputs of similar age from Journal of Biomedical Semantics
#13
of 15 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% 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 21st percentile – i.e., 21% 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 320,940 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.