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Updated: Jul 3, 2026

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

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

Published on: October 13, 2023

Accessing and integrating data and knowledge for biomedical research.

A Burgun¹, O Bodenreider

¹Département d'Information Médicale, CHU Pontchaillou, rue Henri Le Guilloux, F-35033 Rennes Cedex, France. anita.burgun-parenthoine@univ-rennes1.fr

Yearbook of Medical Informatics

|July 30, 2008

Summary

This summary is machine-generated.

Translational research requires integrating diverse biomedical data and knowledge. Addressing challenges in data integration and analysis is crucial for advancing diagnostics, therapeutics, and bioinformatics.

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

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

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:

Biomedical Informatics
Bioinformatics
Medical Informatics

Background:

Translational research integrates basic science with clinical practice.
Advancements in omics sciences present new data integration challenges.

Purpose of the Study:

To review challenges in data and knowledge integration in translational research.
To survey current efforts addressing these integration issues.

Main Methods:

Analysis of biomedical literature to identify trends impacting bioinformatics.
Study of requirements for knowledge repositories and data integration.

Main Results:

Gene expression patterns necessitate new statistical analysis and workflows.
Interoperable repositories with standardized annotations are vital for data pooling and meta-analysis.
Integrated ontologies and knowledge bases enhance data analysis strategies.

Conclusions:

Translational research necessitates integrating research data with clinical data.
Linking omics knowledge with medical knowledge is essential.
Bridging bioinformatics and medical informatics opens new research avenues.