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Related Concept Videos

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
Evolution of Microbial Genome01:08

Evolution of Microbial Genome

Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
Rapid Identification of Pathogens01:25

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MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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Modern Molecular Taxonomy

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Related Experiment Video

Updated: Jun 19, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

GeMInA, Genomic Metadata for Infectious Agents, a geospatial surveillance pathogen database.

Lynn M Schriml1, Cesar Arze, Suvarna Nadendla

  • 1Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. lschriml@som.umaryland.edu

Nucleic Acids Research
|October 24, 2009
PubMed
Summary

The Gemina system integrates pathogen outbreak data, offering a comprehensive tool for investigating infectious diseases. It enhances understanding of pathogen-host interactions and disease spread through metadata analysis and genomic insights.

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Last Updated: Jun 19, 2026

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Epidemiology

Background:

  • Pathogen surveillance and understanding host-pathogen interactions are crucial for public health.
  • Existing data on viral and bacterial pathogens are often fragmented, hindering comprehensive analysis.
  • NIAID Category A-C pathogens pose significant public health threats requiring integrated data systems.

Purpose of the Study:

  • To develop and present the Gemina system, a novel tool for identifying, standardizing, and integrating outbreak metadata.
  • To enhance the understanding of pathogen-host interactions and infectious disease dynamics.
  • To provide an investigative and surveillance platform for NIAID Category A-C pathogens.

Main Methods:

  • Literature text-mining for in-depth data extraction.
  • Integration of outbreak metadata including host, disease, location, and transmission.
  • Development of an extensive ontology and metadata curation processes.
  • Implementation of a web interface for data retrieval and analysis.
  • Utilizing the DNA Signature Insignia Detection Tool for genomic analysis.

Main Results:

  • The Gemina system successfully integrates diverse outbreak metadata, covering Who, What, When, Where, and How for pathogens.
  • It provides a user-friendly web interface for accessing pathogen and host information, including infection systems and incident details.
  • The system facilitates geospatial surveillance and connects pathogens, diseases, and hosts through taxonomic identification.
  • Genomic analysis capabilities are integrated to identify unique genomic regions.

Conclusions:

  • The Gemina system serves as a valuable investigative and geospatial surveillance tool for NIAID Category A-C pathogens.
  • It significantly improves the understanding of pathogen-host interactions and infectious disease epidemiology.
  • The integrated approach of metadata, ontology, and genomic analysis offers a powerful resource for infectious disease research and response.