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Using 16S rRNA gene as marker to detect unknown bacteria in microbial communities

Overview of attention for article published in BMC Bioinformatics, December 2017
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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

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13 X users
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1 patent

Citations

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15 Dimensions

Readers on

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90 Mendeley
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Title
Using 16S rRNA gene as marker to detect unknown bacteria in microbial communities
Published in
BMC Bioinformatics, December 2017
DOI 10.1186/s12859-017-1901-8
Pubmed ID
Authors

Quang Tran, Diem-Trang Pham, Vinhthuy Phan

Abstract

Quantification and identification of microbial genomes based on next-generation sequencing data is a challenging problem in metagenomics. Although current methods have mostly focused on analyzing bacteria whose genomes have been sequenced, such analyses are, however, complicated by the presence of unknown bacteria or bacteria whose genomes have not been sequence. We propose a method for detecting unknown bacteria in environmental samples. Our approach is unique in its utilization of short reads only from 16S rRNA genes, not from entire genomes. We show that short reads from 16S rRNA genes retain sufficient information for detecting unknown bacteria in oral microbial communities. In our experimentation with bacterial genomes from the Human Oral Microbiome Database, we found that this method made accurate and robust predictions at different read coverages and percentages of unknown bacteria. Advantages of this approach include not only a reduction in experimental and computational costs but also a potentially high accuracy across environmental samples due to the strong conservation of the 16S rRNA gene.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 90 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 19%
Student > Bachelor 15 17%
Student > Ph. D. Student 8 9%
Researcher 6 7%
Student > Doctoral Student 4 4%
Other 16 18%
Unknown 24 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 21%
Agricultural and Biological Sciences 17 19%
Immunology and Microbiology 8 9%
Medicine and Dentistry 6 7%
Computer Science 4 4%
Other 9 10%
Unknown 27 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 13 December 2023.
All research outputs
#3,758,495
of 25,626,416 outputs
Outputs from BMC Bioinformatics
#1,263
of 7,732 outputs
Outputs of similar age
#78,496
of 450,612 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 141 outputs
Altmetric has tracked 25,626,416 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,732 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 83% 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 450,612 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 141 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.