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Discovery of physiological and cancer-related regulators of 3′ UTR processing with KAPAC

Overview of attention for article published in Genome Biology, March 2018
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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)
  • Average Attention Score compared to outputs of the same age and source

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29 X users

Citations

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53 Dimensions

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Title
Discovery of physiological and cancer-related regulators of 3′ UTR processing with KAPAC
Published in
Genome Biology, March 2018
DOI 10.1186/s13059-018-1415-3
Pubmed ID
Authors

Andreas J. Gruber, Ralf Schmidt, Souvik Ghosh, Georges Martin, Andreas R. Gruber, Erik van Nimwegen, Mihaela Zavolan

Abstract

3' Untranslated regions (3' UTRs) length is regulated in relation to cellular state. To uncover key regulators of poly(A) site use in specific conditions, we have developed PAQR, a method for quantifying poly(A) site use from RNA sequencing data and KAPAC, an approach that infers activities of oligomeric sequence motifs on poly(A) site choice. Application of PAQR and KAPAC to RNA sequencing data from normal and tumor tissue samples uncovers motifs that can explain changes in cleavage and polyadenylation in specific cancers. In particular, our analysis points to polypyrimidine tract binding protein 1 as a regulator of poly(A) site choice in glioblastoma.

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 34%
Student > Bachelor 11 15%
Student > Master 9 12%
Researcher 5 7%
Professor > Associate Professor 4 5%
Other 6 8%
Unknown 14 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 28%
Biochemistry, Genetics and Molecular Biology 20 27%
Computer Science 5 7%
Medicine and Dentistry 5 7%
Neuroscience 4 5%
Other 4 5%
Unknown 15 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 14 April 2018.
All research outputs
#2,198,954
of 25,382,440 outputs
Outputs from Genome Biology
#1,827
of 4,468 outputs
Outputs of similar age
#46,158
of 344,304 outputs
Outputs of similar age from Genome Biology
#23
of 38 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 59% 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 344,304 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 38 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.