| Title |
bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes
|
|---|---|
| Published in |
Genome Biology, February 2019
|
| DOI | 10.1186/s13059-019-1643-1 |
| Pubmed ID | |
| Authors |
Matthew Z. DeMaere, Aaron E. Darling |
X Demographics
The data shown below were collected from the profiles of 65 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 | 15 | 23% |
| Australia | 13 | 20% |
| United Kingdom | 3 | 5% |
| Austria | 2 | 3% |
| France | 2 | 3% |
| Netherlands | 2 | 3% |
| Denmark | 1 | 2% |
| India | 1 | 2% |
| Russia | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 23 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 38 | 58% |
| Members of the public | 25 | 38% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 94 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 26% |
| Researcher | 18 | 19% |
| Student > Master | 8 | 9% |
| Student > Postgraduate | 7 | 7% |
| Student > Bachelor | 7 | 7% |
| Other | 9 | 10% |
| Unknown | 21 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 33% |
| Biochemistry, Genetics and Molecular Biology | 20 | 21% |
| Computer Science | 7 | 7% |
| Immunology and Microbiology | 4 | 4% |
| Environmental Science | 3 | 3% |
| Other | 3 | 3% |
| Unknown | 26 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 34. 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 05 December 2020.
All research outputs
#1,207,934
of 25,728,350 outputs
Outputs from Genome Biology
#896
of 4,508 outputs
Outputs of similar age
#28,087
of 368,136 outputs
Outputs of similar age from Genome Biology
#18
of 55 outputs
Altmetric has tracked 25,728,350 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,508 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has done well, scoring higher than 80% 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 368,136 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 55 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 67% of its contemporaries.