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Embryonic stem cell-specific signatures in cancer: insights into genomic regulatory networks and implications for medicine

Overview of attention for article published in Genome Medicine, November 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
2 X users
patent
3 patents
facebook
1 Facebook page

Citations

dimensions_citation
109 Dimensions

Readers on

mendeley
157 Mendeley
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Title
Embryonic stem cell-specific signatures in cancer: insights into genomic regulatory networks and implications for medicine
Published in
Genome Medicine, November 2011
DOI 10.1186/gm291
Pubmed ID
Authors

Jonghwan Kim, Stuart H Orkin

Abstract

Embryonic stem (ES) cells are of great interest as a model system for studying early developmental processes and because of their potential therapeutic applications in regenerative medicine. Obtaining a systematic understanding of the mechanisms that control the 'stemness' - self-renewal and pluripotency - of ES cells relies on high-throughput tools to define gene expression and regulatory networks at the genome level. Such recently developed systems biology approaches have revealed highly interconnected networks in which multiple regulatory factors act in combination. Interestingly, stem cells and cancer cells share some properties, notably self-renewal and a block in differentiation. Recently, several groups reported that expression signatures that are specific to ES cells are also found in many human cancers and in mouse cancer models, suggesting that these shared features might inform new approaches for cancer therapy. Here, we briefly summarize the key transcriptional regulators that contribute to the pluripotency of ES cells, the factors that account for the common gene expression patterns of ES and cancer cells, and the implications of these observations for future clinical applications.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 3 2%
United States 2 1%
Germany 1 <1%
Finland 1 <1%
South Africa 1 <1%
Estonia 1 <1%
United Kingdom 1 <1%
Unknown 147 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 25%
Researcher 31 20%
Student > Master 16 10%
Student > Bachelor 11 7%
Other 10 6%
Other 25 16%
Unknown 24 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 40%
Biochemistry, Genetics and Molecular Biology 45 29%
Medicine and Dentistry 13 8%
Computer Science 2 1%
Physics and Astronomy 2 1%
Other 10 6%
Unknown 22 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 02 December 2020.
All research outputs
#1,275,057
of 25,374,647 outputs
Outputs from Genome Medicine
#260
of 1,585 outputs
Outputs of similar age
#7,751
of 246,422 outputs
Outputs of similar age from Genome Medicine
#1
of 18 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,585 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one has done well, scoring higher than 83% 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 246,422 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.