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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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Updated: Jul 5, 2026

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
05:51

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia

Published on: June 15, 2011

Selection of a platform for mutation detection.

Victoria A Joshi1, Debora Mancini-DiNardo, Birgit H Funke

  • 1Harvard Medical School-Partners Healthcare Center for Genetics and Genomics, Cambridge, Massachusetts, USA.

Current Protocols in Human Genetics
|April 23, 2008
PubMed
Summary
This summary is machine-generated.

Choosing the right mutation detection platform is crucial for researchers. This guide helps navigate options, focusing on cost-effectiveness, sensitivity, and throughput for human disease studies.

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Last Updated: Jul 5, 2026

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Published on: March 29, 2017

Area of Science:

  • Genetics and Genomics
  • Biotechnology
  • Molecular Biology

Background:

  • Rapid advancements in mutation detection technologies necessitate cost-effectiveness, improved sensitivity, and higher throughput.
  • The growing number of available mutation detection platforms presents a challenge for researchers in selecting the most suitable option.
  • Understanding the benefits and limitations of each platform is essential for effective mutation analysis.

Purpose of the Study:

  • To provide a practical guide for researchers needing to analyze samples for known or novel mutations.
  • To assist researchers in determining the most appropriate mutation detection platform for their specific needs.
  • To offer an entry point for diverse researchers venturing into mutation analysis.

Main Methods:

  • Overview of various mutation detection platforms.
  • Detailed information on assay parameters, design, and cost considerations.
  • Evaluation of platform flexibility and scalability for different research applications.

Main Results:

  • A structured approach to comparing mutation detection technologies.
  • Consideration of factors beyond technical performance, including economic and practical aspects.
  • Identification of platforms adaptable for both human disease research and other organisms.

Conclusions:

  • Selecting the optimal mutation detection platform requires careful consideration of multiple factors.
  • This guide empowers researchers to make informed decisions based on their unique project requirements.
  • The principles discussed are broadly applicable, extending beyond human disease studies to broader biological research.