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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Non-stem cancer cell kinetics modulate solid tumor progression
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, December 2011
|
| DOI | 10.1186/1742-4682-8-48 |
| Pubmed ID | |
| Authors |
Charles I Morton, Lynn Hlatky, Philip Hahnfeldt, Heiko Enderling |
| Abstract |
Solid tumors are heterogeneous in composition. Cancer stem cells (CSCs) are believed to drive tumor progression, but the relative frequencies of CSCs versus non-stem cancer cells span wide ranges even within tumors arising from the same tissue type. Tumor growth kinetics and composition can be studied through an agent-based cellular automaton model using minimal sets of biological assumptions and parameters. Herein we describe a pivotal role for the generational life span of non-stem cancer cells in modulating solid tumor progression in silico. |
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 | 3 | 60% |
| United Kingdom | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 5% |
| United Kingdom | 1 | 3% |
| Belgium | 1 | 3% |
| Unknown | 36 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 35% |
| Researcher | 9 | 23% |
| Student > Master | 4 | 10% |
| Student > Doctoral Student | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 4 | 10% |
| Unknown | 3 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 33% |
| Medicine and Dentistry | 8 | 20% |
| Physics and Astronomy | 4 | 10% |
| Mathematics | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 4 | 10% |
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 27 February 2015.
All research outputs
#13,175,336
of 23,577,654 outputs
Outputs from Theoretical Biology and Medical Modelling
#125
of 284 outputs
Outputs of similar age
#145,413
of 247,351 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#1
of 4 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 284 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 55% 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 247,351 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them