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State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues?

Overview of attention for article published in BMC Bioinformatics, April 2013
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog
twitter
3 X users

Citations

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63 Dimensions

Readers on

mendeley
120 Mendeley
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2 CiteULike
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Title
State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues?
Published in
BMC Bioinformatics, April 2013
DOI 10.1186/1471-2105-14-s7-s2
Pubmed ID
Authors

Matteo Carrara, Marco Beccuti, Federica Cavallo, Susanna Donatelli, Fulvio Lazzarato, Francesca Cordero, Raffaele A Calogero

Abstract

RNA-seq has the potential to discover genes created by chromosomal rearrangements. Fusion genes, also known as "chimeras", are formed by the breakage and re-joining of two different chromosomes. It is known that chimeras have been implicated in the development of cancer. Few publications in the past showed the presence of fusion events also in normal tissue, but with very limited overlaps between their results. More recently, two fusion genes in normal tissues were detected using both RNA-seq and protein data.Due to heterogeneous results in identifying chimeras in normal tissue, we decided to evaluate the efficacy of state of the art fusion finders in detecting chimeras in RNA-seq data from normal tissues.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 3%
United States 4 3%
France 1 <1%
Norway 1 <1%
Ukraine 1 <1%
Germany 1 <1%
China 1 <1%
Belgium 1 <1%
Unknown 106 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 24%
Student > Ph. D. Student 28 23%
Student > Master 16 13%
Student > Bachelor 9 8%
Student > Doctoral Student 6 5%
Other 15 13%
Unknown 17 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 44%
Biochemistry, Genetics and Molecular Biology 23 19%
Computer Science 10 8%
Medicine and Dentistry 5 4%
Mathematics 2 2%
Other 7 6%
Unknown 20 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 07 November 2013.
All research outputs
#3,588,844
of 22,714,025 outputs
Outputs from BMC Bioinformatics
#1,307
of 7,260 outputs
Outputs of similar age
#30,815
of 196,443 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 120 outputs
Altmetric has tracked 22,714,025 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,260 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 81% 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 196,443 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 84% of its contemporaries.
We're also able to compare this research output to 120 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.