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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modular glycosphere assays for high-throughput functional characterization of influenza viruses
|
|---|---|
| Published in |
BMC Biotechnology, April 2013
|
| DOI | 10.1186/1472-6750-13-34 |
| Pubmed ID | |
| Authors |
Sven N Hobbie, Karthik Viswanathan, Ido Bachelet, Udayanath Aich, Zachary Shriver, Vidya Subramanian, Rahul Raman, Ram Sasisekharan |
| Abstract |
The ongoing global efforts to control influenza epidemics and pandemics require high-throughput technologies to detect, quantify, and functionally characterize viral isolates. The 2009 influenza pandemic as well as the recent in-vitro selection of highly transmissible H5N1 variants have only increased existing concerns about emerging influenza strains with significantly enhanced human-to-human transmissibility. High-affinity binding of the virus hemagglutinin to human receptor glycans is a highly sensitive and stringent indicator of host adaptation and virus transmissibility. The surveillance of receptor-binding characteristics can therefore provide a strong additional indicator for the relative hazard imposed by circulating and newly emerging influenza strains. |
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 % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 5% |
| Unknown | 18 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 32% |
| Student > Bachelor | 3 | 16% |
| Professor | 2 | 11% |
| Student > Master | 2 | 11% |
| Professor > Associate Professor | 2 | 11% |
| Other | 2 | 11% |
| Unknown | 2 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 42% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Immunology and Microbiology | 2 | 11% |
| Computer Science | 1 | 5% |
| Mathematics | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 3 | 16% |
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 16 April 2013.
All research outputs
#18,336,865
of 22,707,247 outputs
Outputs from BMC Biotechnology
#762
of 935 outputs
Outputs of similar age
#149,317
of 197,213 outputs
Outputs of similar age from BMC Biotechnology
#10
of 16 outputs
Altmetric has tracked 22,707,247 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 935 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 9th percentile – i.e., 9% 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 197,213 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.