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Mendeley readers
Attention Score in Context
| Chapter title |
Molecular genotyping of human rhinovirus by using PCR and sanger sequencing.
|
|---|---|
| Chapter number | 4 |
| Book title |
Rhinoviruses
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-1571-2_4 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-1570-5, 978-1-4939-1571-2
|
| Authors |
Wei Wang, Jing He, Yi Liu, Lei Xu, Wencai Guan, Yunwen Hu |
| Abstract |
Human rhinovirus (HRV) is the virus most often associated with acute upper respiratory tract infections. Advances in molecular detection have shown that HRV is also the major viral cause of asthma exacerbations. Genotypic assignment and identification of HRV types are of significant value in the investigation of type-associated differences in disease outcomes, transmission, and epidemiology. Here, we describe a genotyping process involving two separate RT-PCR assays, targeted to VP4/VP2 and 5' UTR regions of HRV genome, respectively. Together with the reference sequences of each HRV species, the generated sequences are used to construct phylogenetic tree for genotyping. |
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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 4 | 20% |
| Student > Doctoral Student | 3 | 15% |
| Student > Bachelor | 3 | 15% |
| Student > Ph. D. Student | 3 | 15% |
| Student > Master | 2 | 10% |
| Other | 5 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 30% |
| Immunology and Microbiology | 4 | 20% |
| Engineering | 3 | 15% |
| Medicine and Dentistry | 3 | 15% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Other | 1 | 5% |
| Unknown | 1 | 5% |
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 28 September 2014.
All research outputs
#20,237,640
of 22,764,165 outputs
Outputs from Methods in molecular biology
#9,866
of 13,089 outputs
Outputs of similar age
#295,617
of 352,895 outputs
Outputs of similar age from Methods in molecular biology
#635
of 996 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,089 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% 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 352,895 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 996 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.