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X Demographics
Mendeley readers
Attention Score in Context
| Title |
I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms
|
|---|---|
| Published in |
Genome Biology, March 2019
|
| DOI | 10.1186/s13059-019-1640-4 |
| Pubmed ID | |
| Authors |
Kin Yau Wong, Cheng Fan, Maki Tanioka, Joel S. Parker, Andrew B. Nobel, Donglin Zeng, Dan-Yu Lin, Charles M. Perou |
X Demographics
The data shown below were collected from the profiles of 19 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 Kingdom | 4 | 21% |
| France | 3 | 16% |
| Australia | 1 | 5% |
| United States | 1 | 5% |
| Spain | 1 | 5% |
| Russia | 1 | 5% |
| India | 1 | 5% |
| Unknown | 7 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 74% |
| Members of the public | 4 | 21% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 29% |
| Researcher | 7 | 20% |
| Student > Bachelor | 2 | 6% |
| Other | 2 | 6% |
| Student > Master | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 12 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 17% |
| Computer Science | 4 | 11% |
| Agricultural and Biological Sciences | 4 | 11% |
| Unspecified | 1 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 6 | 17% |
| Unknown | 13 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 28 August 2019.
All research outputs
#3,711,927
of 25,385,509 outputs
Outputs from Genome Biology
#2,531
of 4,468 outputs
Outputs of similar age
#79,587
of 365,867 outputs
Outputs of similar age from Genome Biology
#47
of 59 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% 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 is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 365,867 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 78% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.