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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving metagenomic binning results with overlapped bins using assembly graphs
|
|---|---|
| Published in |
Algorithms for Molecular Biology, May 2021
|
| DOI | 10.1186/s13015-021-00185-6 |
| Pubmed ID | |
| Authors |
Vijini G. Mallawaarachchi, Anuradha S. Wickramarachchi, Yu Lin |
X Demographics
The data shown below were collected from the profiles of 13 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 | 8% |
| Luxembourg | 1 | 8% |
| France | 1 | 8% |
| Netherlands | 1 | 8% |
| Australia | 1 | 8% |
| Sweden | 1 | 8% |
| Unknown | 7 | 54% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 54% |
| Members of the public | 6 | 46% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 21% |
| Student > Master | 5 | 15% |
| Student > Bachelor | 5 | 15% |
| Researcher | 3 | 9% |
| Student > Doctoral Student | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 12 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 11 | 32% |
| Agricultural and Biological Sciences | 4 | 12% |
| Computer Science | 3 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Unspecified | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 14 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 13 May 2021.
All research outputs
#2,213,275
of 23,577,761 outputs
Outputs from Algorithms for Molecular Biology
#8
of 251 outputs
Outputs of similar age
#57,804
of 440,898 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 7 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 251 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 96% 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 440,898 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 7 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