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Updated: Aug 20, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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GediNET for discovering gene associations across diseases using knowledge based machine learning approach.

Emma Qumsiyeh1, Louise Showe2, Malik Yousef3,4

  • 1Information Technology Engineering, Al-Quds University, Abu Dis, Palestine. emma.qumsiyeh@hotmail.com.

Scientific Reports
|November 19, 2022
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Summary

GediNET integrates prior biological knowledge with machine learning to discover disease-associated genes and novel disease-disease associations. This approach aids in identifying potential biomarkers for improved diagnosis and treatment.

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Machine learning in medicine

Background:

  • Gene discovery for disease biomarkers commonly uses machine learning and feature selection.
  • Integrating prior biological knowledge enhances biomarker discovery for translational applications.

Purpose of the Study:

  • To develop GediNET, a novel approach integrating prior biological knowledge into gene groups for disease association discovery.
  • To enable the discovery of significant associations between diseases using gene signatures.

Main Methods:

  • GediNET integrates prior biological knowledge with gene groups associated with specific diseases.
  • A Grouping, Scoring, and Modelling (G-S-M) process identifies top-performing gene groups.
  • Machine learning models are trained on ranked gene groups to identify disease-disease associations (DDA).

Main Results:

  • GediNET identifies significant associations between diseases based on shared gene signatures.
  • The approach facilitates the discovery of novel relationships between diseases.
  • This facilitates improved diagnostic, prognostic, and therapeutic strategies.

Conclusions:

  • GediNET offers a novel method for discovering disease-associated genes and biomarkers.
  • The approach leverages prior biological knowledge and machine learning for enhanced discovery.
  • GediNET can uncover novel disease-disease associations, advancing precision medicine.