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CRISPR–Cas13 Precision Transcriptome Engineering in Cancer

Overview of attention for article published in Cancer Research, July 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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 blog
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7 X users
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1 patent

Citations

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62 Dimensions

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219 Mendeley
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Title
CRISPR–Cas13 Precision Transcriptome Engineering in Cancer
Published in
Cancer Research, July 2018
DOI 10.1158/0008-5472.can-18-0785
Pubmed ID
Authors

Javier T Granados-Riveron, Guillermo Aquino-Jarquin

Abstract

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated genes (Cas) system has been rapidly harnessed to perform various genomic engineering tasks. Recently, it has been demonstrated that a novel RNA-targeting CRISPR effector protein, called Cas13, binds and cleaves RNA rather than DNA substrates analogously to the eukaryotic RNA interference system. The known Cas13a-Cas13d effectors are able to efficiently cleave complementary target single-stranded RNAs, which represent a potentially safer alternative to deoxyribonuclease Cas9, because it induces loss-of-function phenotypes without genomic loss of the targeted gene. Furthermore, through the improvement in Cas13 effector functionalities, a system called REPAIR has been developed to edit full-length transcripts containing pathogenic mutations, thus providing a promising opportunity for precise base editing. Moreover, advanced engineering of this CRISPR effector also permits nucleic acid detection, allowing the identification of mutations in cell-free tumor DNA through a platform termed Specific High Sensitivity Enzymatic Reporter Unlocking. All of these properties give us a glimpse about the potential of the CRISPR toolkit for precise transcriptome engineering, possibly leading to an expansion of CRISPR technologies for cancer therapeutics and diagnostics. Here, we examine previously unaddressed aspects of the CRISPR-based RNA-targeting approach as a feasible strategy for globally interrogating gene function in cancer in a programmable manner. Cancer Res; 78(15); 1-7. ©2018 AACR.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 219 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 219 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 16%
Student > Bachelor 34 16%
Student > Master 29 13%
Researcher 27 12%
Student > Doctoral Student 11 5%
Other 23 11%
Unknown 60 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 82 37%
Agricultural and Biological Sciences 26 12%
Medicine and Dentistry 10 5%
Immunology and Microbiology 9 4%
Engineering 5 2%
Other 20 9%
Unknown 67 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 28 June 2023.
All research outputs
#2,524,296
of 25,775,807 outputs
Outputs from Cancer Research
#1,852
of 18,888 outputs
Outputs of similar age
#48,798
of 341,788 outputs
Outputs of similar age from Cancer Research
#32
of 502 outputs
Altmetric has tracked 25,775,807 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 18,888 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has done particularly well, scoring higher than 90% 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 341,788 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 85% of its contemporaries.
We're also able to compare this research output to 502 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.