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Dynamics and associations of microbial community types across the human body.

Overview of attention for article published in Nature, April 2014
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

14 news outlets
8 blogs
187 tweeters
1 Facebook page
1 Google+ user
1 Redditor

Readers on

700 Mendeley
14 CiteULike
Dynamics and associations of microbial community types across the human body.
Published in
Nature, April 2014
DOI 10.1038/nature13178
Pubmed ID

Tao Ding, Patrick D. Schloss


A primary goal of the Human Microbiome Project (HMP) was to provide a reference collection of 16S ribosomal RNA gene sequences collected from sites across the human body that would allow microbiologists to better associate changes in the microbiome with changes in health. The HMP Consortium has reported the structure and function of the human microbiome in 300 healthy adults at 18 body sites from a single time point. Using additional data collected over the course of 12-18 months, we used Dirichlet multinomial mixture models to partition the data into community types for each body site and made three important observations. First, there were strong associations between whether individuals had been breastfed as an infant, their gender, and their level of education with their community types at several body sites. Second, although the specific taxonomic compositions of the oral and gut microbiomes were different, the community types observed at these sites were predictive of each other. Finally, over the course of the sampling period, the community types from sites within the oral cavity were the least stable, whereas those in the vagina and gut were the most stable. Our results demonstrate that even with the considerable intra- and interpersonal variation in the human microbiome, this variation can be partitioned into community types that are predictive of each other and are probably the result of life-history characteristics. Understanding the diversity of community types and the mechanisms that result in an individual having a particular type or changing types, will allow us to use their community types to assess disease risk and to personalize therapies.

Twitter Demographics

The data shown below were collected from the profiles of 187 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 700 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 40 6%
Germany 7 1%
Canada 7 1%
France 6 <1%
Denmark 5 <1%
Netherlands 4 <1%
Spain 4 <1%
Russian Federation 3 <1%
United Kingdom 3 <1%
Other 19 3%
Unknown 602 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 206 29%
Researcher 195 28%
Student > Master 86 12%
Student > Bachelor 52 7%
Student > Doctoral Student 39 6%
Other 122 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 393 56%
Medicine and Dentistry 88 13%
Biochemistry, Genetics and Molecular Biology 72 10%
Immunology and Microbiology 31 4%
Computer Science 26 4%
Other 90 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 283. 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 16 March 2018.
All research outputs
of 9,212,752 outputs
Outputs from Nature
of 50,207 outputs
Outputs of similar age
of 171,372 outputs
Outputs of similar age from Nature
of 914 outputs
Altmetric has tracked 9,212,752 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 50,207 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 77.9. This one has done particularly well, scoring higher than 93% 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 171,372 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 99% of its contemporaries.
We're also able to compare this research output to 914 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.