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Tracking Strains in the Microbiome: Insights from Metagenomics and Models

Overview of attention for article published in Frontiers in Microbiology, May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
43 X users
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

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47 Dimensions

Readers on

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244 Mendeley
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Title
Tracking Strains in the Microbiome: Insights from Metagenomics and Models
Published in
Frontiers in Microbiology, May 2016
DOI 10.3389/fmicb.2016.00712
Pubmed ID
Authors

Ilana L. Brito, Eric J. Alm

Abstract

Transmission usually refers to the movement of pathogenic organisms. Yet, commensal microbes that inhabit the human body also move between individuals and environments. Surprisingly little is known about the transmission of these endogenous microbes, despite increasing realizations of their importance for human health. The health impacts arising from the transmission of commensal bacteria range widely, from the prevention of autoimmune disorders to the spread of antibiotic resistance genes. Despite this importance, there are outstanding basic questions: what is the fraction of the microbiome that is transmissible? What are the primary mechanisms of transmission? Which organisms are the most highly transmissible? Higher resolution genomic data is required to accurately link microbial sources (such as environmental reservoirs or other individuals) with sinks (such as a single person's microbiome). New computational advances enable strain-level resolution of organisms from shotgun metagenomic data, allowing the transmission of strains to be followed over time and after discrete exposure events. Here, we highlight the latest techniques that reveal strain-level resolution from raw metagenomic reads and new studies that are tracking strains across people and environments. We also propose how models of pathogenic transmission may be applied to study the movement of commensals between microbial communities.

X Demographics

X Demographics

The data shown below were collected from the profiles of 43 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 244 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
Brazil 2 <1%
Germany 1 <1%
Ireland 1 <1%
United Kingdom 1 <1%
Netherlands 1 <1%
New Zealand 1 <1%
Canada 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 229 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 75 31%
Researcher 55 23%
Student > Master 29 12%
Student > Bachelor 18 7%
Student > Doctoral Student 12 5%
Other 29 12%
Unknown 26 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 88 36%
Biochemistry, Genetics and Molecular Biology 53 22%
Immunology and Microbiology 18 7%
Environmental Science 9 4%
Computer Science 8 3%
Other 35 14%
Unknown 33 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 14 July 2016.
All research outputs
#1,211,405
of 24,885,505 outputs
Outputs from Frontiers in Microbiology
#695
of 28,434 outputs
Outputs of similar age
#22,172
of 341,126 outputs
Outputs of similar age from Frontiers in Microbiology
#25
of 567 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28,434 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done particularly well, scoring higher than 97% 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 341,126 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 567 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.