↓ Skip to main content

CICERO: a versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data

Overview of attention for article published in Genome Biology (Online Edition), May 2020
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)

Mentioned by

news
6 news outlets
blogs
1 blog
twitter
28 tweeters

Citations

dimensions_citation
46 Dimensions

Readers on

mendeley
62 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
CICERO: a versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data
Published in
Genome Biology (Online Edition), May 2020
DOI 10.1186/s13059-020-02043-x
Pubmed ID
Authors

Liqing Tian, Yongjin Li, Michael N. Edmonson, Xin Zhou, Scott Newman, Clay McLeod, Andrew Thrasher, Yu Liu, Bo Tang, Michael C. Rusch, John Easton, Jing Ma, Eric Davis, Austyn Trull, J. Robert Michael, Karol Szlachta, Charles Mullighan, Suzanne J. Baker, James R. Downing, David W. Ellison, Jinghui Zhang

Twitter Demographics

The data shown below were collected from the profiles of 28 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 19%
Student > Ph. D. Student 12 19%
Student > Master 10 16%
Student > Bachelor 4 6%
Student > Doctoral Student 2 3%
Other 4 6%
Unknown 18 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 23%
Agricultural and Biological Sciences 6 10%
Medicine and Dentistry 4 6%
Computer Science 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 9 15%
Unknown 25 40%

Attention Score in Context

This research output has an Altmetric Attention Score of 61. 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 04 July 2020.
All research outputs
#513,564
of 20,767,801 outputs
Outputs from Genome Biology (Online Edition)
#399
of 3,979 outputs
Outputs of similar age
#15,532
of 303,682 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 20,767,801 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,979 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one has done well, scoring higher than 89% 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 303,682 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them