| Title |
Inferring disease associations of the long non-coding RNAs through non-negative matrix factorization
|
|---|---|
| Published in |
Network Modeling Analysis in Health Informatics and Bioinformatics, June 2015
|
| DOI | 10.1007/s13721-015-0081-6 |
| Authors |
Ashis Kumer Biswas, Mingon Kang, Dong-Chul Kim, Chris H. Q. Ding, Baoju Zhang, Xiaoyong Wu, Jean X. Gao |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 44% |
| Student > Doctoral Student | 2 | 22% |
| Student > Bachelor | 1 | 11% |
| Unknown | 2 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 56% |
| Agricultural and Biological Sciences | 1 | 11% |
| Engineering | 1 | 11% |
| Unknown | 2 | 22% |
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 22 June 2015.
All research outputs
#16,291,311
of 23,999,200 outputs
Outputs from Network Modeling Analysis in Health Informatics and Bioinformatics
#22
of 43 outputs
Outputs of similar age
#160,424
of 270,075 outputs
Outputs of similar age from Network Modeling Analysis in Health Informatics and Bioinformatics
#1
of 1 outputs
Altmetric has tracked 23,999,200 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 43 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one scored the same or higher as 21 of them.
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 270,075 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
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