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Combinatorial identification of DNA methylation patterns over age in the human brain

Overview of attention for article published in BMC Bioinformatics, September 2016
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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1 news outlet
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7 X users

Citations

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13 Dimensions

Readers on

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32 Mendeley
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Title
Combinatorial identification of DNA methylation patterns over age in the human brain
Published in
BMC Bioinformatics, September 2016
DOI 10.1186/s12859-016-1259-3
Pubmed ID
Authors

Behrooz Torabi Moghadam, Michal Dabrowski, Bozena Kaminska, Manfred G. Grabherr, Jan Komorowski

Abstract

DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 25%
Researcher 8 25%
Student > Bachelor 3 9%
Professor 3 9%
Student > Master 3 9%
Other 4 13%
Unknown 3 9%
Readers by discipline Count As %
Computer Science 7 22%
Biochemistry, Genetics and Molecular Biology 6 19%
Neuroscience 4 13%
Agricultural and Biological Sciences 4 13%
Medicine and Dentistry 2 6%
Other 6 19%
Unknown 3 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 06 November 2016.
All research outputs
#2,486,643
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#728
of 7,454 outputs
Outputs of similar age
#43,285
of 324,669 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 124 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 90% 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 324,669 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 86% of its contemporaries.
We're also able to compare this research output to 124 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 92% of its contemporaries.