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Related Concept Videos

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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...
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...
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
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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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Candidate gene prioritization.

Ali Masoudi-Nejad1, Alireza Meshkin, Behzad Haji-Eghrari

  • 1Laboratory of Systems Biology and Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. amasoudin@ibb.ut.ac.ir

Molecular Genetics and Genomics : MGG
|August 16, 2012
PubMed
Summary
This summary is machine-generated.

Identifying candidate genes is labor-intensive. This review explores computational methods and algorithms for gene prioritization, aiming to streamline the selection of promising genes for further analysis.

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Area of Science:

  • Genetics and Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Candidate gene identification is a laborious process, traditionally relying on extensive laboratory experiments and fine-mapping studies.
  • Computational methods have emerged to predict and prioritize candidate genes based on sequence characteristics, functional annotations, and similarity to known disease genes.

Purpose of the Study:

  • To review and synthesize the current landscape of computational gene prioritization tools and methodologies.
  • To provide a comprehensive overview of gene prioritization criteria and algorithms for researchers.

Main Methods:

  • Literature review of computational tools and algorithms for candidate gene prioritization.
  • Analysis of existing methods focusing on sequence characteristics, functional annotation, and disease gene similarity.
  • Categorization of prioritization tools into web-based and standalone applications.

Main Results:

  • Numerous computational tools for gene prioritization have been developed in the last decade.
  • These tools employ diverse criteria and algorithms to rank candidate genes based on biological relevance.
  • Both web-based and locally installed applications are available, offering various approaches to gene prioritization.

Conclusions:

  • Computational gene prioritization significantly reduces the labor and cost associated with identifying causative genes.
  • A comprehensive understanding of prioritization criteria and algorithms is crucial for effective candidate gene selection.
  • This review offers a synopsis to guide researchers in selecting appropriate tools for their studies.