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Related Concept Videos

Genetic Screens02:46

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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Related Experiment Video

Updated: May 16, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Optimal vaccination schedule search using genetic algorithm over MPI technology.

Cristiano Calonaci1, Ferdinando Chiacchio, Francesco Pappalardo

  • 1CINECA, Bologna, Italy.

BMC Medical Informatics and Decision Making
|November 15, 2012
PubMed
Summary
This summary is machine-generated.

A novel computational approach optimized the Triplex vaccine schedule for preventing HER-2/neu-driven breast cancer. This optimized schedule, identified through a genetic algorithm, proved effective in vivo, offering a more efficient cancer prevention strategy.

Related Experiment Videos

Last Updated: May 16, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Area of Science:

  • Oncology
  • Immunology
  • Computational Biology

Background:

  • Immunological strategies aim to prevent tumor growth by priming the immune system before cancer onset.
  • Active immunization has successfully prevented virus-related cancers; a new cell vaccine, Triplex, targets HER-2/neu for breast cancer prevention.
  • The Triplex vaccine demonstrated significant efficacy in preventing HER-2/neu-driven mammary carcinogenesis in mice with a lifelong schedule.

Purpose of the Study:

  • To determine the preventive efficacy of the Triplex vaccine using reduced vaccination schedules.
  • To identify an optimal vaccination schedule for the Triplex vaccine through computational modeling.

Main Methods:

  • A computational approach using a parallel genetic algorithm was developed to test various vaccination schedules in silico.
  • The algorithm aimed to find the optimal vaccination schedule for the Triplex vaccine.

Main Results:

  • The computational model successfully identified an optimized vaccination schedule for the Triplex vaccine.
  • In silico testing explored the vast combinatorial space of potential schedules.

Conclusions:

  • The optimized Triplex vaccine schedule, determined computationally, was validated in vivo, yielding positive results.
  • This approach offers a biologically relevant and efficient strategy for HER-2/neu-driven breast cancer prevention.