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Comparison and optimization of CRISPR/dCas9/gRNA genome-labeling systems for live cell imaging

Overview of attention for article published in Genome Biology, March 2018
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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 (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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18 X users
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6 patents

Citations

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54 Dimensions

Readers on

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182 Mendeley
Title
Comparison and optimization of CRISPR/dCas9/gRNA genome-labeling systems for live cell imaging
Published in
Genome Biology, March 2018
DOI 10.1186/s13059-018-1413-5
Pubmed ID
Authors

Yu Hong, Guangqing Lu, Jinzhi Duan, Wenjing Liu, Yu Zhang

Abstract

CRISPR/dCas9 binds precisely to defined genomic sequences through targeting of guide RNA (gRNA) sequences. In vivo imaging of genomic loci can be achieved by recruiting fluorescent proteins using either dCas9 or gRNA. We thoroughly validate and compare the effectiveness and specificity of several dCas9/gRNA genome labeling systems. Surprisingly, we discover that in the gRNA-labeling strategies, accumulation of tagged gRNA transcripts leads to non-specific labeling foci. Furthermore, we develop novel bimolecular fluorescence complementation (BIFC) methods that combine the advantages of both dCas9-labeling and gRNA-labeling strategies. The BIFC-dCas9/gRNA methods demonstrate high signal-to-noise ratios and have no non-specific foci.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 182 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 28%
Researcher 29 16%
Student > Master 16 9%
Student > Bachelor 15 8%
Student > Doctoral Student 9 5%
Other 20 11%
Unknown 42 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 74 41%
Agricultural and Biological Sciences 34 19%
Medicine and Dentistry 4 2%
Neuroscience 4 2%
Physics and Astronomy 3 2%
Other 13 7%
Unknown 50 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 02 April 2024.
All research outputs
#2,286,797
of 25,382,440 outputs
Outputs from Genome Biology
#1,886
of 4,468 outputs
Outputs of similar age
#48,219
of 347,572 outputs
Outputs of similar age from Genome Biology
#27
of 41 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 57% 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 347,572 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 86% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.