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RECLU: a pipeline to discover reproducible transcriptional start sites and their alternative regulation using capped analysis of gene expression (CAGE)

Overview of attention for article published in BMC Genomics, April 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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6 X users
googleplus
1 Google+ user

Citations

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56 Dimensions

Readers on

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100 Mendeley
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Title
RECLU: a pipeline to discover reproducible transcriptional start sites and their alternative regulation using capped analysis of gene expression (CAGE)
Published in
BMC Genomics, April 2014
DOI 10.1186/1471-2164-15-269
Pubmed ID
Authors

Hiroko Ohmiya, Morana Vitezic, Martin C Frith, Masayoshi Itoh, Piero Carninci, Alistair RR Forrest, Yoshihide Hayashizaki, Timo Lassmann, and The FANTOM Consortium

Abstract

Next generation sequencing based technologies are being extensively used to study transcriptomes. Among these, cap analysis of gene expression (CAGE) is specialized in detecting the most 5' ends of RNA molecules. After mapping the sequenced reads back to a reference genome CAGE data highlights the transcriptional start sites (TSSs) and their usage at a single nucleotide resolution.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Japan 2 2%
United States 2 2%
Denmark 1 1%
Italy 1 1%
Luxembourg 1 1%
Unknown 91 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 31%
Student > Ph. D. Student 21 21%
Other 9 9%
Student > Master 9 9%
Professor > Associate Professor 8 8%
Other 13 13%
Unknown 9 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 38%
Biochemistry, Genetics and Molecular Biology 22 22%
Medicine and Dentistry 11 11%
Computer Science 8 8%
Immunology and Microbiology 2 2%
Other 5 5%
Unknown 14 14%
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 13 July 2017.
All research outputs
#6,271,572
of 22,754,104 outputs
Outputs from BMC Genomics
#2,729
of 10,637 outputs
Outputs of similar age
#59,983
of 226,861 outputs
Outputs of similar age from BMC Genomics
#30
of 184 outputs
Altmetric has tracked 22,754,104 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 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 73% 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 226,861 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 73% of its contemporaries.
We're also able to compare this research output to 184 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.