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Future developments in biosensors for field-ready Zika virus diagnostics

Overview of attention for article published in Journal of Biological Engineering, January 2017
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Title
Future developments in biosensors for field-ready Zika virus diagnostics
Published in
Journal of Biological Engineering, January 2017
DOI 10.1186/s13036-016-0046-z
Pubmed ID
Authors

Ariana M. Nicolini, Katherine E. McCracken, Jeong-Yeol Yoon

Abstract

Since early reports of the recent Zika virus outbreak in May 2015, much has been learned and discussed regarding Zika virus infection and transmission. However, many opportunities still remain for translating these findings into field-ready sensors and diagnostics. In this brief review, we discuss current diagnostic methods, consider the prospects of translating other flavivirus biosensors directly to Zika virus sensing, and look toward the future developments needed for high-sensitivity and high-specificity biosensors to come.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Unknown 104 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 18%
Student > Ph. D. Student 15 14%
Student > Bachelor 13 12%
Researcher 10 10%
Student > Doctoral Student 9 9%
Other 19 18%
Unknown 20 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 14%
Agricultural and Biological Sciences 11 10%
Chemistry 11 10%
Engineering 9 9%
Medicine and Dentistry 8 8%
Other 23 22%
Unknown 28 27%
Attention Score in Context

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 27 January 2017.
All research outputs
#18,525,776
of 22,947,506 outputs
Outputs from Journal of Biological Engineering
#213
of 262 outputs
Outputs of similar age
#309,627
of 419,069 outputs
Outputs of similar age from Journal of Biological Engineering
#6
of 8 outputs
Altmetric has tracked 22,947,506 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 262 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 10th percentile – i.e., 10% 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 419,069 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 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.