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Related Concept Videos

Introduction to the Human Microbiota01:22

Introduction to the Human Microbiota

Microorganisms colonize various regions of the human body, including the mouth, nasal passages, throat, stomach, intestines, urogenital tract, and skin. The total number of microbial cells is estimated to range from 10¹³ to 10¹⁴—comparable to, or exceeding, the number of human somatic cells. This host–microbiome relationship has led to the conceptualization of humans as supraorganisms, wherein microbial communities perform vital roles in development, immunity, and disease...
Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

Microbial communities, comprising bacteria, archaea, and eukaryotic microorganisms, inhabit diverse ecosystems and play crucial roles in environmental and biological processes. Their diversity is defined by three main parameters: species richness (the number of distinct species), species abundance (the relative quantity of each species), and species evenness (how uniformly individual species are distributed in various locations). These factors together shape the structure and ecological balance...
Development of Human Microbiota01:30

Development of Human Microbiota

The human microbiota begins developing at birth and undergoes continual change as we age. Infancy marks a critical period of microbial sensitivity, offering a “window of opportunity” during which beneficial microbes help mature the immune system. By age three, children typically develop a more stable and diverse microbial community. Newborns acquire microbes from their immediate environment; vaginal delivery favors maternal vaginal microbes, while cesarean births favor microbes from the skin...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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...
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.
Methods to Assess Microbial Populations01:30

Methods to Assess Microbial Populations

Assessing microbial populations is crucial for understanding microbial roles in health, ecology, and industry. Various complementary techniques—both culture-based and molecular—enable detailed analysis of microbial abundance, diversity, and function.Viable Plate CountThe viable plate count is a traditional culture-based method used to estimate the number of living microbes in a sample. After serial dilution, the sample is spread onto nutrient agar plates. Each viable cell forms a visible...

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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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KG-Microbe - Building Modular and Scalable Knowledge Graphs for Microbiome and Microbial Sciences.

Brook E Santangelo1, Harshad Hegde2, J Harry Caufield2

  • 1Department of Biomedical Informatics, University of Colorado Denver Anschutz Medical Campus, Aurora, CO, USA.

Gigascience
|July 10, 2026
PubMed
Summary

The KG-Microbe framework harmonizes diverse microbial data into a FAIR and AI-ready knowledge graph. This enables integrated analysis across health and environmental domains, uncovering microbial interactions and mechanisms.

Keywords:
genome annotationsknowledge graphsmachine learningmicrobiologymicrobiomeontologiesphenotypessemantic path analysis

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Integrating diverse microbial data is crucial for understanding host-microbe and microbe-microbe interactions impacting health and environment.
  • Challenges include the vast number of microbial species and their complex interactions.
  • Holistic data integration aids in deciphering complex mechanisms and interpreting correlative findings.

Purpose of the Study:

  • To introduce the KG-Microbe framework for harmonizing bacterial and archaeal data.
  • To create Findable, Accessible, Interoperable, and Reusable (FAIR) and AI-ready knowledge graphs (KGs).
  • To support specific use cases like the human microbiome and environmental microbiomes.

Main Methods:

  • Construction of a core KG with organismal traits, environments, and growth preferences.
  • Integration of established ontologies to build a hierarchy of related KGs.
  • Development of customizable taxa subsets for specific research needs.

Main Results:

  • The KG-Microbe framework successfully harmonizes bacterial and archaeal data into FAIR and AI-ready KGs.
  • Evaluations using competency questions confirmed data accuracy and KG utility in studies of inflammatory bowel and Parkinson's diseases.
  • The KGs demonstrated predictive capabilities by explaining microbial growth preferences using graph features.

Conclusions:

  • The KG-Microbe framework unifies microbial data, enabling integrative analyses across biomedical, host, and environmental research.
  • It serves as a flexible, modular technology for both human researchers and machine learning algorithms.
  • Facilitates the discovery of mechanistic explanations for microbial associations.