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A simple algebraic cancer equation: calculating how cancers may arise with normal mutation rates

Overview of attention for article published in BMC Cancer, January 2010
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

twitter
3 X users
wikipedia
8 Wikipedia pages

Citations

dimensions_citation
54 Dimensions

Readers on

mendeley
115 Mendeley
citeulike
3 CiteULike
Title
A simple algebraic cancer equation: calculating how cancers may arise with normal mutation rates
Published in
BMC Cancer, January 2010
DOI 10.1186/1471-2407-10-3
Pubmed ID
Authors

Peter Calabrese, Darryl Shibata

Abstract

The purpose of this article is to present a relatively easy to understand cancer model where transformation occurs when the first cell, among many at risk within a colon, accumulates a set of driver mutations. The analysis of this model yields a simple algebraic equation, which takes as inputs the number of stem cells, mutation and division rates, and the number of driver mutations, and makes predictions about cancer epidemiology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
United Kingdom 2 2%
Germany 1 <1%
France 1 <1%
South Africa 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 104 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 18%
Student > Ph. D. Student 16 14%
Student > Bachelor 14 12%
Student > Master 11 10%
Other 10 9%
Other 18 16%
Unknown 25 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 37%
Biochemistry, Genetics and Molecular Biology 11 10%
Medicine and Dentistry 11 10%
Mathematics 7 6%
Computer Science 3 3%
Other 11 10%
Unknown 29 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 07 January 2023.
All research outputs
#6,119,844
of 23,577,761 outputs
Outputs from BMC Cancer
#1,513
of 8,532 outputs
Outputs of similar age
#39,471
of 167,366 outputs
Outputs of similar age from BMC Cancer
#14
of 29 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 8,532 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 82% 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 167,366 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 29 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 51% of its contemporaries.