| Title |
Accurate prediction of protein-lncRNA interactions by diffusion and HeteSim features across heterogeneous network
|
|---|---|
| Published in |
BMC Bioinformatics, October 2018
|
| DOI | 10.1186/s12859-018-2390-0 |
| Pubmed ID | |
| Authors |
Lei Deng, Junqiang Wang, Yun Xiao, Zixiang Wang, Hui Liu |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
| France | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 20% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Bachelor | 3 | 10% |
| Student > Master | 3 | 10% |
| Student > Doctoral Student | 2 | 7% |
| Other | 4 | 13% |
| Unknown | 8 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 23% |
| Biochemistry, Genetics and Molecular Biology | 6 | 20% |
| Computer Science | 3 | 10% |
| Immunology and Microbiology | 2 | 7% |
| Business, Management and Accounting | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 9 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 October 2018.
All research outputs
#14,142,343
of 23,106,390 outputs
Outputs from BMC Bioinformatics
#4,521
of 7,330 outputs
Outputs of similar age
#185,286
of 346,144 outputs
Outputs of similar age from BMC Bioinformatics
#76
of 118 outputs
Altmetric has tracked 23,106,390 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% 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 35th percentile – i.e., 35% 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 346,144 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.