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Related Concept Videos

Genetic Screens02:46

Genetic Screens

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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.
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...
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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Genetic Variation01:25

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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Related Experiment Video

Updated: Jun 17, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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GENEVIC: GENetic data Exploration and Visualization via Intelligent interactive Console.

Anindita Nath1, Savannah Mwesigwa1, Yulin Dai1

  • 1Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.

Bioinformatics (Oxford, England)
|August 8, 2024
PubMed
Summary

GENEVIC, an AI chat framework, simplifies genetic data analysis for biologists. It automates tasks like variant prioritization and literature searches, accelerating biomedical discovery.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Artificial Intelligence in Medicine

Background:

  • The exponential growth of genetic data presents challenges for knowledge extraction.
  • Efficiently analyzing and interpreting large-scale genetic information is crucial for biomedical research.

Purpose of the Study:

  • To introduce GENEVIC, an AI-driven chat framework designed to bridge the gap between genetic data and biomedical knowledge discovery.
  • To provide a user-friendly, automated tool for genetic data analysis and interpretation.

Main Methods:

  • Leveraging generative AI (ChatGPT) for automated analysis, retrieval, and visualization of genetic information.
  • Integrating functionalities for protein interaction network generation, gene set enrichment, and literature searches (PubMed, Google Scholar, arXiv).
  • Pilot testing using a curated database of genetic variants associated with Alzheimer's disease, schizophrenia, and cognition, ranked by Polygenic Score (PGS) Catalog effect weights.

Main Results:

  • GENEVIC successfully automates complex genetic data analysis tasks.
  • The framework enables efficient prioritization of genetic variants in complex diseases.
  • User-friendly interface and HIPAA-compliant infrastructure ensure accessibility and security.

Conclusions:

  • GENEVIC serves as a biologist's copilot, streamlining genetic research.
  • The prototype advances genetic research by enabling informed biomedical decisions.
  • GENEVIC enhances the efficiency of uncovering valuable knowledge from vast genetic datasets.