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Related Concept Videos

Introduction to Language of Pathophysiology l01:25

Introduction to Language of Pathophysiology l

Pathophysiology investigates how biological mechanisms—typically starting at the cellular level—disrupt normal bodily functions. It bridges anatomy and physiology to explain the progression of disease. With this foundation, it is important to understand the following key terms used to describe disease processes: Diagnosis:The process of identifying a disease using clinical evaluation, including signs (objective evidence like rashes), symptoms (subjective experiences like pain), laboratory test...
Introduction to Language of Pathophysiology ll01:17

Introduction to Language of Pathophysiology ll

This lesson explores key terms that describe how diseases progress, their outcomes, and their distribution in populations.Diagnostic tests identify diseases and monitor treatment. These include blood and urine tests, biopsies, imaging (X-ray, MRI), and detection of infectious agents.Remission is a reduction or disappearance of symptoms.Exacerbation refers to the worsening of symptoms, such as increased wheezing during an asthma attack.A precipitating factor triggers an acute episode, while a...
Methods of Classification and Identification01:28

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...

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Related Experiment Video

Updated: Jun 27, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Building a knowledge base for systems pathology.

Holger Michael1, Jennifer Hogan, Alexander Kel

  • 1Department of Bioinformatics, Goldschmidtstr. 1, D-37077 Göttingen, Germany.

Briefings in Bioinformatics
|December 17, 2008
PubMed
Summary
This summary is machine-generated.

Developing omics data repositories into knowledge sources is key for personalized medicine. This approach enables a systemic view of molecular disease causes, advancing systems pathology.

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Related Experiment Videos

Last Updated: Jun 27, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics
  • Systems Biology

Background:

  • The exponential growth of omics data presents a significant hurdle for personalized medicine.
  • Integrating diverse omics datasets into actionable knowledge remains a complex challenge.

Purpose of the Study:

  • To present strategies for transforming omics data repositories into accessible knowledge sources.
  • To establish a foundation for systems pathology by enabling a systemic view of molecular disease causes.
  • To utilize diabetes as a specific use case to demonstrate these strategies.

Main Methods:

  • Developing computational frameworks for data integration.
  • Implementing knowledge extraction techniques from large-scale omics datasets.
  • Establishing data repositories with standardized formats for interoperability.

Main Results:

  • Demonstrated a methodology for converting raw omics data into structured knowledge.
  • Showcased the application of this methodology using diabetes as a use case.
  • Provided a blueprint for creating computer-accessible knowledge sources.

Conclusions:

  • The proposed strategies facilitate the translation of omics data into valuable knowledge for personalized medicine.
  • This approach lays the groundwork for systems pathology, enabling a holistic understanding of disease mechanisms.
  • Effective data repository development is crucial for advancing precision health.