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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
CICERO: a versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data
|
|---|---|
| Published in |
Genome Biology, 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 |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 41% |
| United Kingdom | 3 | 11% |
| Germany | 2 | 7% |
| Hong Kong | 1 | 4% |
| Ireland | 1 | 4% |
| Switzerland | 1 | 4% |
| Unknown | 8 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 16 | 59% |
| Members of the public | 8 | 30% |
| Science communicators (journalists, bloggers, editors) | 2 | 7% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 16% |
| Researcher | 12 | 15% |
| Student > Master | 11 | 14% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 4 | 5% |
| Other | 5 | 6% |
| Unknown | 28 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 18 | 23% |
| Medicine and Dentistry | 7 | 9% |
| Agricultural and Biological Sciences | 6 | 8% |
| Engineering | 3 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Other | 9 | 11% |
| Unknown | 34 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 57. 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
#745,144
of 25,387,668 outputs
Outputs from Genome Biology
#488
of 4,470 outputs
Outputs of similar age
#23,104
of 430,335 outputs
Outputs of similar age from Genome Biology
#16
of 78 outputs
Altmetric has tracked 25,387,668 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 4,470 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 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 430,335 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 78 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.