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Pan-cancer patterns of DNA methylation

Overview of attention for article published in Genome Medicine, August 2014
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

1 news outlet
1 blog
6 tweeters
3 patents


121 Dimensions

Readers on

183 Mendeley
1 CiteULike
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Pan-cancer patterns of DNA methylation
Published in
Genome Medicine, August 2014
DOI 10.1186/s13073-014-0066-6
Pubmed ID

Tania Witte, Christoph Plass, Clarissa Gerhauser


The comparison of DNA methylation patterns across cancer types (pan-cancer methylome analyses) has revealed distinct subgroups of tumors that share similar methylation patterns. Integration of these data with the wealth of information derived from cancer genome profiling studies performed by large international consortia has provided novel insights into the cellular aberrations that contribute to cancer development. There is evidence that genetic mutations in epigenetic regulators (such as DNMT3, IDH1/2 or H3.3) mediate or contribute to these patterns, although a unifying molecular mechanism underlying the global alterations of DNA methylation has largely been elusive. Knowledge gained from pan-cancer methylome analyses will aid the development of diagnostic and prognostic biomarkers, improve patient stratification and the discovery of novel druggable targets for therapy, and will generate hypotheses for innovative clinical trial designs based on methylation subgroups rather than on cancer subtypes. In this review, we discuss recent advances in the global profiling of tumor genomes for aberrant DNA methylation and the integration of these data with cancer genome profiling data, highlight potential mechanisms leading to different methylation subgroups, and show how this information can be used in basic research and for translational applications. A remaining challenge is to experimentally prove the functional link between observed pan-cancer methylation patterns, the associated genetic aberrations, and their relevance for the development of cancer.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 183 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 1%
Brazil 2 1%
India 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 176 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 26%
Researcher 34 19%
Student > Master 25 14%
Student > Doctoral Student 12 7%
Student > Bachelor 12 7%
Other 28 15%
Unknown 24 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 56 31%
Agricultural and Biological Sciences 54 30%
Medicine and Dentistry 22 12%
Computer Science 5 3%
Chemistry 5 3%
Other 12 7%
Unknown 29 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 18 March 2021.
All research outputs
of 20,513,123 outputs
Outputs from Genome Medicine
of 1,329 outputs
Outputs of similar age
of 213,992 outputs
Outputs of similar age from Genome Medicine
of 38 outputs
Altmetric has tracked 20,513,123 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 1,329 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. 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 213,992 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 93% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.