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Assessing and Interpreting the Within-Body Biogeography of Human Microbiome Diversity

Overview of attention for article published in Frontiers in Microbiology, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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1 blog
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Title
Assessing and Interpreting the Within-Body Biogeography of Human Microbiome Diversity
Published in
Frontiers in Microbiology, August 2018
DOI 10.3389/fmicb.2018.01619
Pubmed ID
Authors

Zhanshan Ma, Lianwei Li, Wendy Li

Abstract

A human body hosts a relatively independent microbiome including five major regional biomes (i.e., airway, oral, gut, skin, and urogenital). Each of them may possess different regional characteristics with important implications to our health and diseases (i.e., so-termed microbiome associated diseases). Nevertheless, these regional microbiomes are connected with each other through diffusions and migrations. Here, we investigate the within-body (intra-individual) distribution feature of microbiome diversity via diversity area relationship (DAR) modeling, which, to the best of our knowledge, has not been systematically studied previously. We utilized the Hill numbers for measuring alpha and beta-diversities and built 1,200 within-body DAR models with to date the most comprehensive human microbiome datasets of 18 sites from the human microbiome project (HMP) cohort. We established the intra-DAR profile (z-q pattern: the diversity scaling parameter z of the power law (PL) at diversity order q = 0-3), intra-PDO (pair-wise diversity overlap) profile (g-q), and intra-MAD (maximal accrual diversity) profile (Dmax-q) for the within-body biogeography of the human microbiome. These profiles constitute the "maps" of the within-body biogeography, and offer important insights on the within-body distribution of the human microbiome. Furthermore, we investigated the heterogeneity among individuals in their biogeography parameters and found that there is not an "average Joe" that can represent majority of individuals in a cohort or population. For example, we found that most individuals in the HMP cohort have relatively lower maximal accrual diversity (MAD) or in the "long tail" of the so-termed power law distribution. In the meantime, there are a small number of individuals in the cohort who possess disproportionally higher MAD values. These findings may have important implications for personalized medicine of the human microbiome associated diseases in practice, besides their theoretical significance in microbiome research such as establishing the baseline for the conservation of human microbiome.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 17%
Student > Ph. D. Student 5 14%
Professor 4 11%
Student > Master 4 11%
Student > Bachelor 3 9%
Other 5 14%
Unknown 8 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 20%
Medicine and Dentistry 6 17%
Immunology and Microbiology 3 9%
Agricultural and Biological Sciences 3 9%
Unspecified 1 3%
Other 6 17%
Unknown 9 26%
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 08 October 2022.
All research outputs
#4,164,191
of 25,443,857 outputs
Outputs from Frontiers in Microbiology
#3,743
of 29,374 outputs
Outputs of similar age
#73,822
of 340,961 outputs
Outputs of similar age from Frontiers in Microbiology
#159
of 749 outputs
Altmetric has tracked 25,443,857 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 29,374 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 well, scoring higher than 87% 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 340,961 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 78% of its contemporaries.
We're also able to compare this research output to 749 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.