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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, January 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 (97th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
2 tweeters
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
94 Dimensions

Readers on

mendeley
147 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, January 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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 147 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 137 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 28%
Researcher 30 20%
Student > Master 16 11%
Student > Bachelor 11 7%
Other 9 6%
Other 22 15%
Unknown 18 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 43%
Biochemistry, Genetics and Molecular Biology 42 29%
Medicine and Dentistry 11 7%
Computer Science 3 2%
Engineering 2 1%
Other 9 6%
Unknown 17 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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
#985,316
of 19,539,469 outputs
Outputs from Genome Medicine
#216
of 1,289 outputs
Outputs of similar age
#8,176
of 233,690 outputs
Outputs of similar age from Genome Medicine
#2
of 35 outputs
Altmetric has tracked 19,539,469 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 1,289 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. 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 233,690 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 35 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 97% of its contemporaries.