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Related Concept Videos

Genetic Screens02:46

Genetic Screens

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.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
Pharmacogenetics and Pharmacogenomics: Overview01:29

Pharmacogenetics and Pharmacogenomics: Overview

Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...

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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
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Published on: November 12, 2012

Prioritizing functional modules mediating genetic perturbations and their phenotypic effects: a global strategy.

Li Wang1, Fengzhu Sun, Ting Chen

  • 1Molecular and Computational Biology, Department of Biology Sciences, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089-2910, USA. wang7@usc.edu

Genome Biology
|December 18, 2008
PubMed
Summary

This study introduces a Bayesian network strategy to identify key biological modules responsible for genetic changes and their effects. The approach effectively highlights conserved lethality modules and reveals novel cancer-related processes.

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Area of Science:

  • Systems biology
  • Computational biology
  • Genetics

Background:

  • Identifying functional modules affected by genetic perturbations is crucial for understanding biological processes.
  • Overlapping candidate modules complicate the precise identification of key pathways.
  • Prioritizing these modules is essential for interpreting phenotypic effects.

Purpose of the Study:

  • To develop a global strategy for prioritizing functional modules involved in genetic perturbations.
  • To apply a Bayesian network framework to effectively analyze overlapping candidate modules.
  • To demonstrate the approach's utility using examples of lethality in Saccharomyces cerevisiae and human cancer.

Main Methods:

  • Developed a Bayesian network framework for module prioritization.
  • Applied the strategy to analyze genetic perturbations and their phenotypic outcomes.
  • Utilized Saccharomyces cerevisiae lethality and human cancer data for validation.

Main Results:

  • The Bayesian network approach successfully prioritized functional modules.
  • Lethality was found to be more conserved at the module level than at the gene level.
  • Identified several novel biological processes potentially linked to human cancer.

Conclusions:

  • The developed Bayesian network strategy is effective for prioritizing functional modules in genetic studies.
  • Module-level conservation offers a valuable perspective for understanding conserved biological functions.
  • The findings provide new insights into cancer-related biological processes.