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Updated: Jun 4, 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

The ROBOKOP v1.0 knowledge graph system for exploring relationships between biomedical entities.

Karamarie Fecho1,2, Evan Morris3, Jon-Michael Beasley4

  • 1Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. kfecho@copperlineprofessionalsolutions.com.

Scientific Reports
|June 2, 2026
PubMed
Summary
This summary is machine-generated.

ROBOKOP is an open-source biomedical knowledge graph system that integrates diverse data sources. Its v1.0 release offers enhanced exploration of biological pathways and disease associations.

Keywords:
Application programming interfaceBiomedical discoveryKnowledge graphReasoning algorithmUser interface

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

Published on: June 13, 2025

Related Experiment Videos

Last Updated: Jun 4, 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

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:

  • Biomedical Informatics
  • Knowledge Representation
  • Data Integration

Background:

  • Biomedical research generates vast, complex data.
  • Integrating disparate knowledge sources remains a challenge.
  • A unified system is needed for efficient data exploration.

Purpose of the Study:

  • Introduce ROBOKOP v1.0, a biomedical knowledge graph system.
  • Describe its components and functionalities.
  • Demonstrate its utility through diverse use cases.

Main Methods:

  • Developed ROBOKOP, a modular, KG-based system.
  • Utilized ORION pipeline for data standardization and integration.
  • Leveraged Biolink Model for KG schema and ontology.

Main Results:

  • Released ROBOKOP v1.0 with enhanced features.
  • Demonstrated successful integration of multiple knowledge sources.
  • Showcased applications in asthma gene target validation and environmental exposure studies.

Conclusions:

  • ROBOKOP provides a powerful, accessible platform for biomedical knowledge exploration.
  • The system facilitates discovery of complex biological relationships.
  • Its modular design supports ongoing development and diverse applications.