You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Tigmint: correcting assembly errors using linked reads from large molecules
|
|---|---|
| Published in |
BMC Bioinformatics, October 2018
|
| DOI | 10.1186/s12859-018-2425-6 |
| Pubmed ID | |
| Authors |
Shaun D. Jackman, Lauren Coombe, Justin Chu, Rene L. Warren, Benjamin P. Vandervalk, Sarah Yeo, Zhuyi Xue, Hamid Mohamadi, Joerg Bohlmann, Steven J.M. Jones, Inanc Birol |
X Demographics
The data shown below were collected from the profiles of 59 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 | 9 | 15% |
| United Kingdom | 7 | 12% |
| Canada | 5 | 8% |
| Germany | 4 | 7% |
| Australia | 3 | 5% |
| New Zealand | 2 | 3% |
| France | 2 | 3% |
| Finland | 1 | 2% |
| Singapore | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 21 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 39 | 66% |
| Members of the public | 20 | 34% |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 92 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 25% |
| Researcher | 18 | 20% |
| Student > Master | 10 | 11% |
| Student > Bachelor | 8 | 9% |
| Student > Doctoral Student | 7 | 8% |
| Other | 4 | 4% |
| Unknown | 22 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 35% |
| Biochemistry, Genetics and Molecular Biology | 21 | 23% |
| Computer Science | 7 | 8% |
| Medicine and Dentistry | 2 | 2% |
| Immunology and Microbiology | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 24 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 31. 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 04 March 2020.
All research outputs
#1,177,698
of 23,850,698 outputs
Outputs from BMC Bioinformatics
#137
of 7,475 outputs
Outputs of similar age
#26,817
of 353,149 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 134 outputs
Altmetric has tracked 23,850,698 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 7,475 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 done particularly well, scoring higher than 98% 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 353,149 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 134 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.