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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GKLOMLI: a link prediction model for inferring miRNA–lncRNA interactions by using Gaussian kernel-based method on network profile and linear optimization algorithm
|
|---|---|
| Published in |
BMC Bioinformatics, May 2023
|
| DOI | 10.1186/s12859-023-05309-w |
| Pubmed ID | |
| Authors |
Leon Wong, Lei Wang, Zhu-Hong You, Chang-An Yuan, Yu-An Huang, Mei-Yuan Cao |
X Demographics
The data shown below were collected from the profiles of 7 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 States | 1 | 14% |
| India | 1 | 14% |
| United Kingdom | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 43% |
| Members of the public | 3 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 1 | 13% |
| Student > Ph. D. Student | 1 | 13% |
| Student > Master | 1 | 13% |
| Unknown | 5 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemical Engineering | 1 | 13% |
| Unspecified | 1 | 13% |
| Biochemistry, Genetics and Molecular Biology | 1 | 13% |
| Computer Science | 1 | 13% |
| Unknown | 4 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 15 May 2023.
All research outputs
#8,083,095
of 24,262,436 outputs
Outputs from BMC Bioinformatics
#3,124
of 7,510 outputs
Outputs of similar age
#135,667
of 379,992 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 126 outputs
Altmetric has tracked 24,262,436 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,510 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 50% 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 379,992 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 61% of its contemporaries.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.