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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
1 blog
twitter
7 tweeters

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
199 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.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 199 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 33 17%
Student > Ph. D. Student 30 15%
Researcher 27 14%
Student > Master 25 13%
Student > Doctoral Student 10 5%
Other 22 11%
Unknown 52 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 75 38%
Agricultural and Biological Sciences 26 13%
Medicine and Dentistry 10 5%
Immunology and Microbiology 7 4%
Engineering 4 2%
Other 16 8%
Unknown 61 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 2022.
All research outputs
#2,513,295
of 21,685,809 outputs
Outputs from Cancer Research
#2,089
of 17,463 outputs
Outputs of similar age
#52,196
of 299,321 outputs
Outputs of similar age from Cancer Research
#30
of 458 outputs
Altmetric has tracked 21,685,809 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,463 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done well, scoring higher than 88% 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 299,321 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 458 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.