| Title |
CELDA - an ontology for the comprehensive representation of cells in complex systems
|
|---|---|
| Published in |
BMC Bioinformatics, July 2013
|
| DOI | 10.1186/1471-2105-14-228 |
| Pubmed ID | |
| Authors |
Stefanie Seltmann, Harald Stachelscheid, Alexander Damaschun, Ludger Jansen, Fritz Lekschas, Jean-Fred Fontaine, Throng Nghia Nguyen-Dobinsky, Ulf Leser, Andreas Kurtz |
| Abstract |
The need for detailed description and modeling of cells drives the continuous generation of large and diverse datasets. Unfortunately, there exists no systematic and comprehensive way to organize these datasets and their information. CELDA (Cell: Expression, Localization, Development, Anatomy) is a novel ontology for the association of primary experimental data and derived knowledge to various types of cells of organisms. |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Germany | 1 | 4% |
| Unknown | 24 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 38% |
| Student > Master | 5 | 19% |
| Student > Ph. D. Student | 4 | 15% |
| Student > Bachelor | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 3 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 31% |
| Computer Science | 5 | 19% |
| Biochemistry, Genetics and Molecular Biology | 4 | 15% |
| Medicine and Dentistry | 4 | 15% |
| Mathematics | 1 | 4% |
| Other | 4 | 15% |
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 06 April 2014.
All research outputs
#7,455,523
of 22,792,160 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,280 outputs
Outputs of similar age
#57,750
of 172,309 outputs
Outputs of similar age from BMC Bioinformatics
#46
of 95 outputs
Altmetric has tracked 22,792,160 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
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 172,309 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 95 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.