Related Experiment Video
Updated: Jan 6, 2026
03:08
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
861
De Novo Pathway Enrichment with KeyPathwayMiner
Nicolas Alcaraz1, Anne Hartebrodt2, Markus List3
1Department of Biology, The Bioinformatics Centre, University of Copenhagen, Copenhagen, Denmark.
Methods in Molecular Biology (Clifton, N.J.)
|October 5, 2019
Summary
KeyPathwayMiner integrates molecular networks with omics data to identify disease-related gene subnetworks. This approach captures dynamic biological changes missed by static network analysis, aiding complex disease research.
Area of Science:
- Systems biology
- Bioinformatics
- Genomics
Background:
- Static biomolecular networks fail to capture dynamic changes in complex diseases.
- Understanding gene and protein interactions is crucial for disease mechanism elucidation.
Purpose of the Study:
- To introduce KeyPathwayMiner, a software platform for dynamic network analysis.
- To integrate prior knowledge from molecular interaction networks with multi-omics data.
- To extract disease-relevant subnetworks with a high number of deregulated genes.
Main Methods:
- Integration of molecular interaction networks with various OMICS datasets (e.g., DNA microarrays, RNA sequencing, methylation data).
- Utilizing the KeyPathwayMiner software platform.
- Analysis performed within the Cytoscape network analysis tool and a standalone web application.
Main Results:
- KeyPathwayMiner enables the extraction of connected subnetworks enriched with deregulated genes.
- The platform facilitates the identification of dynamic changes in gene expression and regulation during disease development.
- Successful integration of multi-omics data for network-based disease subnetwork discovery.
Conclusions:
- KeyPathwayMiner effectively addresses the limitations of static networks in complex disease research.
- The software provides a robust method for integrated multi-omics network analysis.
- This approach enhances the understanding of disease pathogenesis by identifying key deregulated pathways.
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