↓ Skip to main content

Whole-genome sequencing targets drug-resistant bacterial infections

Overview of attention for article published in Human Genomics, August 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
15 X users

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
308 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Whole-genome sequencing targets drug-resistant bacterial infections
Published in
Human Genomics, August 2015
DOI 10.1186/s40246-015-0037-z
Pubmed ID
Authors

N. V. Punina, N. M. Makridakis, M. A. Remnev, A. F. Topunov

Abstract

During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today's WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users 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 308 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Australia 2 <1%
Denmark 1 <1%
Sweden 1 <1%
Unknown 302 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 61 20%
Student > Master 51 17%
Researcher 48 16%
Student > Bachelor 28 9%
Other 19 6%
Other 44 14%
Unknown 57 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 75 24%
Biochemistry, Genetics and Molecular Biology 63 20%
Immunology and Microbiology 27 9%
Medicine and Dentistry 26 8%
Veterinary Science and Veterinary Medicine 10 3%
Other 44 14%
Unknown 63 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 January 2018.
All research outputs
#4,278,895
of 25,371,288 outputs
Outputs from Human Genomics
#107
of 564 outputs
Outputs of similar age
#50,407
of 275,650 outputs
Outputs of similar age from Human Genomics
#3
of 11 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 81% of its peers.
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 275,650 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.