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Related Concept Videos

In-vitro Mutagenesis01:16

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

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Related Experiment Video

Updated: Jul 4, 2026

Selection-dependent and Independent Generation of CRISPR/Cas9-mediated Gene Knockouts in Mammalian Cells
11:35

Selection-dependent and Independent Generation of CRISPR/Cas9-mediated Gene Knockouts in Mammalian Cells

Published on: June 16, 2017

Can single knockouts accurately single out gene functions?

David Deutscher1, Isaac Meilijson, Stefan Schuster

  • 1Google Haifa, Haifa, Israel. ddeutscher@gmail.com

BMC Systems Biology
|June 20, 2008
PubMed
Summary

Analyzing gene function in yeast requires multiple gene knockouts, not just single ones. Single-gene studies miss key contributors to organism growth and metabolic functions, leading to incomplete understanding.

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Pooled CRISPR-Based Genetic Screens in Mammalian Cells
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Last Updated: Jul 4, 2026

Selection-dependent and Independent Generation of CRISPR/Cas9-mediated Gene Knockouts in Mammalian Cells
11:35

Selection-dependent and Independent Generation of CRISPR/Cas9-mediated Gene Knockouts in Mammalian Cells

Published on: June 16, 2017

Using a Fluorescent PCR-capillary Gel Electrophoresis Technique to Genotype CRISPR/Cas9-mediated Knockout Mutants in a High-throughput Format
08:25

Using a Fluorescent PCR-capillary Gel Electrophoresis Technique to Genotype CRISPR/Cas9-mediated Knockout Mutants in a High-throughput Format

Published on: April 8, 2017

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

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Published on: September 4, 2019

Area of Science:

  • Systems biology
  • Metabolic engineering
  • Computational biology

Background:

  • Localizing function in complex biological systems is crucial for understanding tasks.
  • Traditional knockout studies often perturb only one element, potentially missing system-level insights due to interactions and redundancy.

Purpose of the Study:

  • To quantify the limitations of single-perturbation analysis in biological systems.
  • To compare the findings of single-perturbation analysis with a comprehensive multiple-perturbation approach.

Main Methods:

  • Utilized a novel quantitative analysis of multiple knockouts based on Shapley values from game theory.
  • Employed an established in-silico model of Saccharomyces cerevisiae metabolism.

Main Results:

  • Single-perturbation analysis missed at least 33% of genes significant for yeast growth.
  • While single-perturbations identified essential genes, they were insufficient for detailed metabolic function assignment.
  • A multiple-perturbation approach proved essential for accurate functional annotation.

Conclusions:

  • Multiple-perturbation analysis provides a richer, more biologically plausible functional map of yeast metabolic networks.
  • This approach is vital for a comprehensive understanding of gene contributions in complex biological systems.