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Related Concept Videos

CRISPR01:59

CRISPR

Genome editing technologies allow scientists to modify an organism’s DNA via the addition, removal, or rearrangement of genetic material at specific genomic locations. These types of techniques could potentially be used to cure genetic disorders such as hemophilia and sickle cell anemia. One popular and widely used DNA-editing research tool that could lead to safe and effective cures for genetic disorders is the CRISPR-Cas9 system. CRISPR-Cas9 stands for Clustered Regularly Interspaced Short...
CRISPR01:59

CRISPR

Genome editing technologies allow scientists to modify an organism’s DNA via the addition, removal, or rearrangement of genetic material at specific genomic locations. These types of techniques could potentially be used to cure genetic disorders such as hemophilia and sickle cell anemia. One popular and widely used DNA-editing research tool that could lead to safe and effective cures for genetic disorders is the CRISPR-Cas9 system. CRISPR-Cas9 stands for Clustered Regularly Interspaced Short...
CRISPR and crRNAs02:53

CRISPR and crRNAs

Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
The CRISPR-Cas system stores a copy of foreign DNA in the host genome and uses it to identify the foreign DNA upon reinfection. CRISPR-Cas has three different...
CRISPR/Cas9 Genome Editing01:28

CRISPR/Cas9 Genome Editing

The CRISPR-Cas system serves as a bacterial defense mechanism against invading genetic elements such as viruses and plasmids, forming the foundation for its adaptation as a powerful genome-editing tool. Originally discovered in prokaryotes, this system has been repurposed to revolutionize genetic engineering across a wide range of organisms, including plants, animals, and humans. The core component, Cas9, is an endonuclease derived from Streptococcus pyogenes, capable of introducing...

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Related Experiment Video

Updated: Jul 1, 2026

Pooled CRISPR-Based Genetic Screens in Mammalian Cells
09:05

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Published on: September 4, 2019

Computational tool choice impacts CRISPR spacer-protospacer detection.

Uri Neri1, Antonio Pedro Camargo1, Brian Bushnell1

  • 1Department of Energy, Joint Genome Institute, Berkeley, CA 94720, United States.

Bioinformatics (Oxford, England)
|June 29, 2026
PubMed
Summary

Benchmarking CRISPR spacer-protospacer matching tools reveals significant differences in performance. This study provides practical defaults and clarifies trade-offs for microbial and viromics analyses.

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CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
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CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

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Last Updated: Jul 1, 2026

Pooled CRISPR-Based Genetic Screens in Mammalian Cells
09:05

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Published on: September 4, 2019

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

Area of Science:

  • Microbiology
  • Viromics
  • Bioinformatics

Background:

  • CRISPR spacer-protospacer matching is crucial for inferring host-virus interactions.
  • Current sequence search tools are often under-evaluated for this specific application.

Purpose of the Study:

  • To benchmark commonly used sequence search and alignment tools for CRISPR spacer-protospacer matching.
  • To evaluate tool performance across various datasets and reporting behaviors.

Main Methods:

  • Utilized synthetic, semi-synthetic, and real-world datasets for benchmarking.
  • Assessed tools based on recall, runtime, and resource usage across different distance metrics and thresholds.

Main Results:

  • Observed substantial performance differences among commonly used tools.
  • Identified significant variations in recall, runtime, and resource consumption.
  • Provided practical default settings for large-scale spacer-target matching.

Conclusions:

  • The choice of tool and its configuration significantly impacts the accuracy of host-virus interaction inference.
  • Clarified trade-offs between exhaustive and heuristic approaches for spacer-target matching.
  • Recommendations are provided for optimizing CRISPR-based microbial and viromics studies.