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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Methodology for Identifying Host Factors Involved in West Nile Virus Infection
|
|---|---|
| Chapter number | 10 |
| Book title |
West Nile Virus
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3670-0_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3668-7, 978-1-4939-3670-0
|
| Authors |
Manoj N. Krishnan |
| Abstract |
The West Nile virus (WNV) infection is a major medical problem for humans and some domesticated animals. WNV infection of host cells involves the interplay of the virus with several host factors. Identification of the host factors impacting on WNV infection can enhance our understanding of virus infection mechanisms, host immune defense mechanisms, and also reveal novel host targets that can be developed as antivirals. RNA interference (RNAi) is a highly efficient genetic tool to discover host genes involved in WNV infection at a genome scale. Here, we describe a protocol for conducting human genome wide RNAi screen to discover novel host factors associated with WNV infection of human cells. |
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 % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 1 | 14% |
| Professor | 1 | 14% |
| Student > Ph. D. Student | 1 | 14% |
| Student > Master | 1 | 14% |
| Researcher | 1 | 14% |
| Other | 1 | 14% |
| Unknown | 1 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 43% |
| Agricultural and Biological Sciences | 1 | 14% |
| Immunology and Microbiology | 1 | 14% |
| Unknown | 2 | 29% |
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 December 2017.
All research outputs
#18,578,649
of 23,011,300 outputs
Outputs from Methods in molecular biology
#7,962
of 13,157 outputs
Outputs of similar age
#285,655
of 394,694 outputs
Outputs of similar age from Methods in molecular biology
#845
of 1,471 outputs
Altmetric has tracked 23,011,300 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 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% 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 394,694 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,471 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.