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X Demographics
Mendeley readers
Attention Score in Context
| Title |
WholeCellViz: data visualization for whole-cell models
|
|---|---|
| Published in |
BMC Bioinformatics, August 2013
|
| DOI | 10.1186/1471-2105-14-253 |
| Pubmed ID | |
| Authors |
Ruby Lee, Jonathan R Karr, Markus W Covert |
| Abstract |
Whole-cell models promise to accelerate biomedical science and engineering. However, discovering new biology from whole-cell models and other high-throughput technologies requires novel tools for exploring and analyzing complex, high-dimensional data. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| Sweden | 1 | 20% |
| United Kingdom | 1 | 20% |
| Japan | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Cuba | 1 | 1% |
| Australia | 1 | 1% |
| Singapore | 1 | 1% |
| Brazil | 1 | 1% |
| Spain | 1 | 1% |
| Russia | 1 | 1% |
| Unknown | 91 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 31% |
| Student > Ph. D. Student | 20 | 20% |
| Student > Master | 13 | 13% |
| Student > Bachelor | 9 | 9% |
| Student > Doctoral Student | 5 | 5% |
| Other | 15 | 15% |
| Unknown | 6 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 29 | 29% |
| Computer Science | 18 | 18% |
| Biochemistry, Genetics and Molecular Biology | 14 | 14% |
| Engineering | 8 | 8% |
| Mathematics | 4 | 4% |
| Other | 15 | 15% |
| Unknown | 11 | 11% |
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 22 September 2016.
All research outputs
#13,822,239
of 24,143,470 outputs
Outputs from BMC Bioinformatics
#3,896
of 7,506 outputs
Outputs of similar age
#104,236
of 203,519 outputs
Outputs of similar age from BMC Bioinformatics
#42
of 81 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,506 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 203,519 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.