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Related Concept Videos

Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

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Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Related Experiment Video

Updated: Sep 11, 2025

Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging
09:31

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Microbiome knowledge graph as a tool to understand bacteria-host associations.

Anand Eruvessi Pudavar1, Krishanu Das Baksi1, Vatsala Pokhrel1,2,3

  • 1TCS Research, Tata Consultancy Services Ltd, TCS SP2 SEZ, Hinjewadi Phase 3, Pune, 411057, India.

Archives of Microbiology
|August 12, 2025
PubMed
Summary

This study presents a method for building a microbiome-centric Knowledge Graph (KG) to integrate gut bacteria-host interactions. This approach enhances microbiome data analysis and hypothesis generation for researchers.

Keywords:
Bacteria-host associationBioinformaticsKnowledge graphKnowledge graph question answeringMicrobiome

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Area of Science:

  • Microbiome research
  • Bioinformatics
  • Computational biology

Background:

  • Gut bacteria significantly impact human health and physiology.
  • Knowledge Graphs (KGs) can integrate complex gut bacteria-host associations.
  • Limited resources exist for constructing KGs for microbiome domain experts.

Purpose of the Study:

  • To outline a methodology for constructing a microbiome-centric KG.
  • To demonstrate how KGs enhance conventional microbiome data analysis.
  • To provide a protocol for KG construction and utilization for hypothesis generation.

Main Methods:

  • Data collection, entity/relationship selection, and preprocessing for KG construction.
  • Implementation of KG construction using Resource Description Framework (RDF) and Labeled Property Graph (LPG) models.
  • Comparison of querying techniques and application of KG in biological case studies.

Main Results:

  • A comprehensive protocol for building a microbiome-centric KG is detailed.
  • Demonstration of KG construction in both RDF and LPG formats.
  • Successful application of the KG for microbiome data analysis and hypothesis generation.

Conclusions:

  • The developed methodology provides a complete protocol for microbiome-centric KG construction.
  • KGs offer a powerful tool for integrating and analyzing complex microbiome data.
  • This work empowers domain experts to leverage KGs for advanced microbiome research.