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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Coexpression analysis of large cancer datasets provides insight into the cellular phenotypes of the tumour microenvironment
|
|---|---|
| Published in |
BMC Genomics, July 2013
|
| DOI | 10.1186/1471-2164-14-469 |
| Pubmed ID | |
| Authors |
Tamasin N Doig, David A Hume, Thanasis Theocharidis, John R Goodlad, Christopher D Gregory, Tom C Freeman |
| Abstract |
Biopsies taken from individual tumours exhibit extensive differences in their cellular composition due to the inherent heterogeneity of cancers and vagaries of sample collection. As a result genes expressed in specific cell types, or associated with certain biological processes are detected at widely variable levels across samples in transcriptomic analyses. This heterogeneity also means that the level of expression of genes expressed specifically in a given cell type or process, will vary in line with the number of those cells within samples or activity of the pathway, and will therefore be correlated in their expression. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 5% |
| United Kingdom | 2 | 3% |
| Spain | 1 | 2% |
| Norway | 1 | 2% |
| Unknown | 52 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 19% |
| Researcher | 11 | 19% |
| Student > Doctoral Student | 4 | 7% |
| Professor > Associate Professor | 4 | 7% |
| Student > Master | 4 | 7% |
| Other | 10 | 17% |
| Unknown | 15 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 27% |
| Biochemistry, Genetics and Molecular Biology | 13 | 22% |
| Computer Science | 4 | 7% |
| Immunology and Microbiology | 3 | 5% |
| Medicine and Dentistry | 3 | 5% |
| Other | 5 | 8% |
| Unknown | 15 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 October 2017.
All research outputs
#7,345,736
of 23,881,329 outputs
Outputs from BMC Genomics
#3,321
of 10,793 outputs
Outputs of similar age
#60,254
of 196,877 outputs
Outputs of similar age from BMC Genomics
#36
of 117 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 67% 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 196,877 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 67% of its contemporaries.
We're also able to compare this research output to 117 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 69% of its contemporaries.