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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FluShuffle and FluResort: new algorithms to identify reassorted strains of the influenza virus by mass spectrometry
|
|---|---|
| Published in |
BMC Bioinformatics, August 2012
|
| DOI | 10.1186/1471-2105-13-208 |
| Pubmed ID | |
| Authors |
Aaron TL Lun, Jason WH Wong, Kevin M Downard |
| Abstract |
Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 3% |
| United States | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 26 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 28% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Postgraduate | 4 | 14% |
| Student > Bachelor | 2 | 7% |
| Student > Doctoral Student | 1 | 3% |
| Other | 6 | 21% |
| Unknown | 3 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 31% |
| Biochemistry, Genetics and Molecular Biology | 5 | 17% |
| Medicine and Dentistry | 5 | 17% |
| Computer Science | 2 | 7% |
| Veterinary Science and Veterinary Medicine | 1 | 3% |
| Other | 4 | 14% |
| Unknown | 3 | 10% |
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 21 August 2012.
All research outputs
#18,313,878
of 22,675,759 outputs
Outputs from BMC Bioinformatics
#6,285
of 7,249 outputs
Outputs of similar age
#129,626
of 169,121 outputs
Outputs of similar age from BMC Bioinformatics
#79
of 101 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,249 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 5th percentile – i.e., 5% 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 169,121 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.