Title |
Predicting links between tumor samples and genes using 2-Layered graph based diffusion approach
|
---|---|
Published in |
BMC Bioinformatics, September 2019
|
DOI | 10.1186/s12859-019-3056-2 |
Pubmed ID | |
Authors |
Mohan Timilsina, Haixuan Yang, Ratnesh Sahay, Dietrich Rebholz-Schuhmann |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Ireland | 2 | 33% |
United Kingdom | 1 | 17% |
United States | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 50% |
Scientists | 2 | 33% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 11 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 4 | 36% |
Student > Ph. D. Student | 1 | 9% |
Student > Doctoral Student | 1 | 9% |
Researcher | 1 | 9% |
Unknown | 4 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 2 | 18% |
Biochemistry, Genetics and Molecular Biology | 2 | 18% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 9% |
Agricultural and Biological Sciences | 1 | 9% |
Nursing and Health Professions | 1 | 9% |
Other | 0 | 0% |
Unknown | 4 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 09 November 2019.
All research outputs
#6,977,148
of 23,163,378 outputs
Outputs from BMC Bioinformatics
#2,685
of 7,341 outputs
Outputs of similar age
#122,323
of 340,917 outputs
Outputs of similar age from BMC Bioinformatics
#47
of 93 outputs
Altmetric has tracked 23,163,378 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,341 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 gotten more attention than average, scoring higher than 63% 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 340,917 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 63% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.