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Diversity and enterotype in gut bacterial community of adults in Taiwan

Overview of attention for article published in BMC Genomics, January 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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1 blog
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Citations

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55 Dimensions

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116 Mendeley
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1 CiteULike
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Title
Diversity and enterotype in gut bacterial community of adults in Taiwan
Published in
BMC Genomics, January 2017
DOI 10.1186/s12864-016-3261-6
Pubmed ID
Authors

Chao Liang, Han-Chi Tseng, Hui-Mei Chen, Wei-Chi Wang, Chih-Min Chiu, Jen-Yun Chang, Kuan-Yi Lu, Shun-Long Weng, Tzu-Hao Chang, Chao-Hsiang Chang, Chen-Tsung Weng, Hwei-Ming Wang, Hsien-Da Huang

Abstract

Gastrointestinal microbiota, particularly gut microbiota, is associated with human health. The biodiversity of gut microbiota is affected by ethnicities and environmental factors such as dietary habits or medicine intake, and three enterotypes of the human gut microbiome were announced in 2011. These enterotypes are not significantly correlated with gender, age, or body weight but are influenced by long-term dietary habits. However, to date, only two enterotypes (predominantly consisting of Bacteroides and Prevotella) have shown these characteristics in previous research; the third enterotype remains ambiguous. Understanding the enterotypes can improve the knowledge of the relationship between microbiota and human health. We obtained 181 human fecal samples from adults in Taiwan. Microbiota compositions were analyzed using next-generation sequencing (NGS) technology, which is a culture-independent method of constructing microbial community profiles by sequencing 16S ribosomal DNA (rDNA). In these samples, 17,675,898 sequencing reads were sequenced, and on average, 215 operational taxonomic units (OTUs) were identified for each sample. In this study, the major bacteria in the enterotypes identified from the fecal samples were Bacteroides, Prevotella, and Enterobacteriaceae, and their correlation with dietary habits was confirmed. A microbial interaction network in the gut was observed on the basis of the amount of short-chain fatty acids, pH value of the intestine, and composition of the bacterial community (enterotypes). Finally, a decision tree was derived to provide a predictive model for the three enterotypes. The accuracies of this model in training and independent testing sets were 97.2 and 84.0%, respectively. We used NGS technology to characterize the microbiota and constructed a predictive model. The most significant finding was that Enterobacteriaceae, the predominant subtype, could be a new subtype of enterotypes in the Asian population.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Unknown 115 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 15%
Student > Master 17 15%
Student > Ph. D. Student 16 14%
Student > Bachelor 12 10%
Other 7 6%
Other 14 12%
Unknown 33 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 20%
Medicine and Dentistry 17 15%
Biochemistry, Genetics and Molecular Biology 16 14%
Nursing and Health Professions 5 4%
Business, Management and Accounting 2 2%
Other 13 11%
Unknown 40 34%
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 12 September 2017.
All research outputs
#3,850,750
of 23,885,338 outputs
Outputs from BMC Genomics
#1,440
of 10,855 outputs
Outputs of similar age
#75,075
of 424,421 outputs
Outputs of similar age from BMC Genomics
#40
of 208 outputs
Altmetric has tracked 23,885,338 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 10,855 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 86% 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 424,421 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 82% of its contemporaries.
We're also able to compare this research output to 208 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.