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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2014
|
| DOI | 10.1186/1471-2105-15-240 |
| Pubmed ID | |
| Authors |
Justin Feigelman, Fabian J Theis, Carsten Marr |
| Abstract |
Biological data often originate from samples containing mixtures of subpopulations, corresponding e.g. to distinct cellular phenotypes. However, identification of distinct subpopulations may be difficult if biological measurements yield distributions that are not easily separable. |
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 % |
|---|---|---|
| Norway | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 2% |
| United States | 1 | 2% |
| Sweden | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 58 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 29% |
| Student > Ph. D. Student | 15 | 24% |
| Professor > Associate Professor | 8 | 13% |
| Student > Bachelor | 5 | 8% |
| Other | 4 | 6% |
| Other | 8 | 13% |
| Unknown | 4 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 42% |
| Biochemistry, Genetics and Molecular Biology | 11 | 18% |
| Computer Science | 6 | 10% |
| Engineering | 3 | 5% |
| Immunology and Microbiology | 2 | 3% |
| Other | 11 | 18% |
| Unknown | 3 | 5% |
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 11 July 2014.
All research outputs
#17,723,043
of 22,758,248 outputs
Outputs from BMC Bioinformatics
#5,927
of 7,272 outputs
Outputs of similar age
#153,631
of 226,417 outputs
Outputs of similar age from BMC Bioinformatics
#101
of 140 outputs
Altmetric has tracked 22,758,248 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,272 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 13th percentile – i.e., 13% 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 226,417 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 140 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.