| Title |
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method
|
|---|---|
| Published in |
BMC Bioinformatics, January 2019
|
| DOI | 10.1186/s12859-018-2575-6 |
| Pubmed ID | |
| Authors |
Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang, Ling-Yun Dai |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 25% |
| Student > Master | 4 | 13% |
| Student > Bachelor | 4 | 13% |
| Other | 1 | 3% |
| Student > Doctoral Student | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 13 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 31% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Chemical Engineering | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 13 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 05 January 2019.
All research outputs
#20,547,611
of 23,122,481 outputs
Outputs from BMC Bioinformatics
#6,905
of 7,330 outputs
Outputs of similar age
#370,179
of 435,934 outputs
Outputs of similar age from BMC Bioinformatics
#193
of 211 outputs
Altmetric has tracked 23,122,481 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,330 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% 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 435,934 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 211 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.