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Related Concept Videos

Gene Therapy00:59

Gene Therapy

Gene therapy is a technique where a gene is inserted into a person’s cells to prevent or treat a serious disease. The added gene may be a healthy version of the gene that is mutated in the patient, or it could be a different gene that inactivates or compensates for the patient’s disease-causing gene. For example, in patients with severe combined immunodeficiency (SCID) due to a mutation in the gene for the enzyme adenosine deaminase, a functioning version of the gene can be inserted. The...
Gene Therapy00:59

Gene Therapy

Gene therapy is a technique where a gene is inserted into a person’s cells to prevent or treat a serious disease. The added gene may be a healthy version of the gene that is mutated in the patient, or it could be a different gene that inactivates or compensates for the patient’s disease-causing gene. For example, in patients with severe combined immunodeficiency (SCID) due to a mutation in the gene for the enzyme adenosine deaminase, a functioning version of the gene can be inserted. The...
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...
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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...
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...

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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

Chapter 15: disease gene prioritization.

Yana Bromberg1

  • 1Department of Biochemistry and Microbiology, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, New Jersey, USA. YanaB@rci.rutgers.edu

Plos Computational Biology
|May 2, 2013
PubMed
Summary
This summary is machine-generated.

Prioritizing candidate disease genes computationally saves time and resources. Advanced methods are needed to analyze high-throughput data for faster disease gene discovery and development of new treatments.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Identifying disease genes is crucial for understanding genetic disorders.
  • Experimental validation of causal gene-disease links is costly and time-intensive.
  • Computational gene prioritization offers a cost-effective strategy to narrow down candidate genes.

Purpose of the Study:

  • To highlight the importance of computational gene prioritization in reducing the cost and time of experimental validation.
  • To emphasize the need for advanced computational methods to handle large datasets from high-throughput experiments.
  • To underscore the role of gene prioritization in accelerating the discovery of diagnostics and treatments for diseases.

Main Methods:

  • Utilizes correlative evidence linking genes to diseases.
  • Incorporates data from high-throughput experimentation.
  • Employs computational approaches for gene prioritization.

Main Results:

  • Existing gene prioritization techniques improve experimental study outcomes.
  • Computational methods help manage and interpret large volumes of biological data.
  • Prioritization strategies reduce the scope of experimental validation.

Conclusions:

  • Computational gene prioritization is essential for efficient disease gene discovery.
  • Development of faster, more reliable prioritization methods is critical.
  • Improved techniques will aid in developing novel diagnostics and treatments for diseases.