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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis
|
|---|---|
| Published in |
Genome Biology, December 2014
|
| DOI | 10.1186/s13059-014-0525-9 |
| Pubmed ID | |
| Authors |
Assieh Saadatpour, Guoji Guo, Stuart H Orkin, Guo-Cheng Yuan |
| Abstract |
A fundamental challenge for cancer therapy is that each tumor contains a highly heterogeneous cell population whose structure and mechanistic underpinnings remain incompletely understood. Recent advances in single-cell gene expression profiling have created new possibilities to characterize this heterogeneity and to dissect the potential intra-cancer cellular hierarchy. |
X Demographics
The data shown below were collected from the profiles of 4 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 Kingdom | 3 | 75% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 2 | 50% |
| Members of the public | 1 | 25% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 1% |
| United States | 2 | 1% |
| Sweden | 1 | <1% |
| France | 1 | <1% |
| Unknown | 152 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 54 | 34% |
| Researcher | 34 | 22% |
| Student > Bachelor | 15 | 9% |
| Student > Master | 13 | 8% |
| Student > Postgraduate | 10 | 6% |
| Other | 14 | 9% |
| Unknown | 18 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 55 | 35% |
| Biochemistry, Genetics and Molecular Biology | 48 | 30% |
| Medicine and Dentistry | 10 | 6% |
| Computer Science | 8 | 5% |
| Immunology and Microbiology | 4 | 3% |
| Other | 11 | 7% |
| Unknown | 22 | 14% |
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 18 December 2014.
All research outputs
#14,915,476
of 25,374,917 outputs
Outputs from Genome Biology
#3,897
of 4,467 outputs
Outputs of similar age
#188,215
of 368,291 outputs
Outputs of similar age from Genome Biology
#91
of 101 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 12th percentile – i.e., 12% 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 368,291 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 101 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.