↓ Skip to main content

A semi-supervised approach uncovers thousands of intragenic enhancers differentially activated in human cells

Overview of attention for article published in BMC Genomics, July 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
10 X users
facebook
1 Facebook page

Readers on

mendeley
40 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A semi-supervised approach uncovers thousands of intragenic enhancers differentially activated in human cells
Published in
BMC Genomics, July 2015
DOI 10.1186/s12864-015-1704-0
Pubmed ID
Authors

Juan González-Vallinas, Amadís Pagès, Babita Singh, Eduardo Eyras

Abstract

Transcriptional enhancers are generally known to regulate gene transcription from afar. Their activation involves a series of changes in chromatin marks and recruitment of protein factors. These enhancers may also occur inside genes, but how many may be active in human cells and their effects on the regulation of the host gene remains unclear. We describe a novel semi-supervised method based on the relative enrichment of chromatin signals between 2 conditions to predict active enhancers. We applied this method to the tumoral K562 and the normal GM12878 cell lines to predict enhancers that are differentially active in one cell type. These predictions show enhancer-like properties according to positional distribution, correlation with gene expression and production of enhancer RNAs. Using this model, we predict 10,365 and 9777 intragenic active enhancers in K562 and GM12878, respectively, and relate the differential activation of these enhancers to expression and splicing differences of the host genes. We propose that the activation or silencing of intragenic transcriptional enhancers modulate the regulation of the host gene by means of a local change of the chromatin and the recruitment of enhancer-related factors that may interact with the RNA directly or through the interaction with RNA binding proteins. Predicted enhancers are available at http://regulatorygenomics.upf.edu/Projects/enhancers.html .

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Spain 1 3%
China 1 3%
Germany 1 3%
Unknown 36 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 40%
Student > Master 8 20%
Researcher 3 8%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 5 13%
Unknown 4 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 50%
Biochemistry, Genetics and Molecular Biology 13 33%
Computer Science 2 5%
Medicine and Dentistry 1 3%
Unknown 4 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 17 December 2017.
All research outputs
#6,806,248
of 24,846,849 outputs
Outputs from BMC Genomics
#2,739
of 11,087 outputs
Outputs of similar age
#73,146
of 268,121 outputs
Outputs of similar age from BMC Genomics
#77
of 254 outputs
Altmetric has tracked 24,846,849 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 11,087 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 75% 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 268,121 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.