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X Demographics
Mendeley readers
Attention Score in Context
| Title |
REW-ISA: unveiling local functional blocks in epi-transcriptome profiling data via an RNA expression-weighted iterative signature algorithm
|
|---|---|
| Published in |
BMC Bioinformatics, October 2020
|
| DOI | 10.1186/s12859-020-03787-w |
| Pubmed ID | |
| Authors |
Lin Zhang, Shutao Chen, Jingyi Zhu, Jia Meng, 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 % |
|---|---|---|
| India | 1 | 25% |
| Sweden | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 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 % |
|---|---|---|
| Researcher | 2 | 22% |
| Student > Bachelor | 2 | 22% |
| Other | 1 | 11% |
| Lecturer | 1 | 11% |
| Student > Doctoral Student | 1 | 11% |
| Other | 2 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 33% |
| Biochemistry, Genetics and Molecular Biology | 2 | 22% |
| Nursing and Health Professions | 1 | 11% |
| Psychology | 1 | 11% |
| Engineering | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 1 | 11% |
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 11 October 2020.
All research outputs
#14,720,444
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#4,813
of 7,400 outputs
Outputs of similar age
#230,282
of 417,388 outputs
Outputs of similar age from BMC Bioinformatics
#111
of 176 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 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 30th percentile – i.e., 30% 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 417,388 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 176 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.