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Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level

Overview of attention for article published in Frontiers in Microbiology, September 2017
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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8 X users

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137 Mendeley
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Title
Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level
Published in
Frontiers in Microbiology, September 2017
DOI 10.3389/fmicb.2017.01831
Pubmed ID
Authors

Zixi Chen, Lei Chen, Weiwen Zhang

Abstract

Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microbiology studies to single-cell level. With recent technological advances, such as flow cytometry, next-generation sequencing (NGS), and microspectroscopy, single-cell microbiology has greatly enhanced the understanding of individuality and heterogeneity of microbes in many biological systems. Notably, the application of multiple 'omics' in single-cell analysis has shed light on how individual cells perceive, respond, and adapt to the environment, how heterogeneity arises under external stress and finally determines the fate of the whole population, and how microbes survive under natural conditions. As single-cell analysis involves no axenic cultivation of target microorganism, it has also been demonstrated as a valuable tool for dissecting the microbial 'dark matter.' In this review, current state-of-the-art tools and methods for genomic and transcriptomic analysis of microbes at single-cell level were critically summarized, including single-cell isolation methods and experimental strategies of single-cell analysis with NGS. In addition, perspectives on the future trends of technology development in the field of single-cell analysis was also presented.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 137 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 20%
Researcher 22 16%
Student > Bachelor 19 14%
Student > Master 18 13%
Student > Doctoral Student 6 4%
Other 21 15%
Unknown 24 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 25%
Biochemistry, Genetics and Molecular Biology 29 21%
Immunology and Microbiology 12 9%
Environmental Science 8 6%
Engineering 4 3%
Other 17 12%
Unknown 33 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 04 November 2017.
All research outputs
#7,097,916
of 26,393,590 outputs
Outputs from Frontiers in Microbiology
#6,466
of 30,263 outputs
Outputs of similar age
#99,568
of 329,999 outputs
Outputs of similar age from Frontiers in Microbiology
#191
of 506 outputs
Altmetric has tracked 26,393,590 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 30,263 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done well, scoring higher than 78% 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 329,999 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 506 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.