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Cell cycle correlated genes dictate the prognostic power of breast cancer gene lists.

Overview of attention for article published in BMC Medical Genomics, April 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#47 of 346)
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
59 Dimensions

Readers on

mendeley
25 Mendeley
citeulike
2 CiteULike
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Title
Cell cycle correlated genes dictate the prognostic power of breast cancer gene lists.
Published in
BMC Medical Genomics, April 2008
DOI 10.1186/1755-8794-1-11
Pubmed ID
Authors

Mosley JD, Keri RA

Abstract

Numerous gene lists or "classifiers" have been derived from global gene expression data that assign breast cancers to good and poor prognosis groups. A remarkable feature of these molecular signatures is that they have few genes in common, prompting speculation that they may use distinct genes to measure the same pathophysiological process(es), such as proliferation. However, this supposition has not been rigorously tested. If gene-based classifiers function by measuring a minimal number of cellular processes, we hypothesized that the informative genes for these processes could be identified and the data sets could be adjusted for the predictive contributions of those genes. Such adjustment would then attenuate the predictive function of any signature measuring that same process.

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Spain 1 4%
Unknown 23 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 40%
Student > Ph. D. Student 6 24%
Other 3 12%
Student > Doctoral Student 2 8%
Lecturer > Senior Lecturer 1 4%
Other 2 8%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 28%
Medicine and Dentistry 6 24%
Biochemistry, Genetics and Molecular Biology 4 16%
Computer Science 3 12%
Mathematics 1 4%
Other 2 8%
Unknown 2 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 09 February 2011.
All research outputs
#627,647
of 5,037,615 outputs
Outputs from BMC Medical Genomics
#47
of 346 outputs
Outputs of similar age
#13,133
of 93,635 outputs
Outputs of similar age from BMC Medical Genomics
#3
of 16 outputs
Altmetric has tracked 5,037,615 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 346 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 86% 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 93,635 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 85% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.