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 |
GenESysV: a fast, intuitive and scalable genome exploration open source tool for variants generated from high-throughput sequencing projects
|
|---|---|
| Published in |
BMC Bioinformatics, January 2019
|
| DOI | 10.1186/s12859-019-2636-5 |
| Pubmed ID | |
| Authors |
Mohammad Zia, Paul Spurgeon, Adrian Levesque, Thomas Furlani, Jianxin Wang |
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 % |
|---|---|---|
| United Kingdom | 2 | 50% |
| Sweden | 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 23% |
| Student > Ph. D. Student | 7 | 20% |
| Other | 5 | 14% |
| Student > Master | 4 | 11% |
| Student > Bachelor | 3 | 9% |
| Other | 3 | 9% |
| Unknown | 5 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 37% |
| Agricultural and Biological Sciences | 5 | 14% |
| Computer Science | 5 | 14% |
| Medicine and Dentistry | 3 | 9% |
| Immunology and Microbiology | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 February 2019.
All research outputs
#15,559,348
of 23,125,690 outputs
Outputs from BMC Bioinformatics
#5,417
of 7,334 outputs
Outputs of similar age
#265,501
of 437,790 outputs
Outputs of similar age from BMC Bioinformatics
#136
of 202 outputs
Altmetric has tracked 23,125,690 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,334 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 18th percentile – i.e., 18% 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 437,790 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 202 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.