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Genomic analysis of emerging pathogens: methods, application and future trends

Overview of attention for article published in Genome Biology (Online Edition), November 2014
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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 (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

blogs
1 blog
twitter
13 tweeters
facebook
4 Facebook pages
googleplus
2 Google+ users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
160 Mendeley
citeulike
2 CiteULike
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Title
Genomic analysis of emerging pathogens: methods, application and future trends
Published in
Genome Biology (Online Edition), November 2014
DOI 10.1186/s13059-014-0541-9
Pubmed ID
Authors

Lucy M Li, Nicholas C Grassly, Christophe Fraser

Abstract

The number of emerging infectious diseases is increasing. Characterizing novel or re-emerging infections is aided by the availability of pathogen genomes. In this review, we evaluate methods that exploit pathogen sequences and the contribution of genomic analysis to understand the epidemiology of recently emerged infectious diseases.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Brazil 2 1%
Sweden 2 1%
Uruguay 1 <1%
Australia 1 <1%
Norway 1 <1%
Vietnam 1 <1%
United Kingdom 1 <1%
Taiwan 1 <1%
Other 3 2%
Unknown 144 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 25%
Student > Ph. D. Student 34 21%
Student > Master 21 13%
Student > Bachelor 17 11%
Other 10 6%
Other 24 15%
Unknown 14 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 61 38%
Biochemistry, Genetics and Molecular Biology 33 21%
Medicine and Dentistry 17 11%
Immunology and Microbiology 7 4%
Mathematics 7 4%
Other 13 8%
Unknown 22 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 July 2015.
All research outputs
#1,006,738
of 16,578,610 outputs
Outputs from Genome Biology (Online Edition)
#986
of 3,495 outputs
Outputs of similar age
#19,506
of 311,544 outputs
Outputs of similar age from Genome Biology (Online Edition)
#29
of 88 outputs
Altmetric has tracked 16,578,610 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,495 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.3. This one has gotten more attention than average, scoring higher than 71% 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 311,544 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 88 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 68% of its contemporaries.