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MBC PathNet: integration and visualization of networks connecting functionally related pathways predicted from
Jens Hansen1,2, Ravi Iyengar1,2
1Mount Sinai Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States.
Bioinformatics Advances
|September 8, 2025
Summary
Molecular Biology of the Cell Pathway Networks (PathNet) integrates and visualizes pathway data from gene and protein lists. This tool aids in exploring shared and distinct biological mechanisms across multiple datasets.
Area of Science:
- Molecular Biology
- Bioinformatics
- Systems Biology
Background:
- High-throughput technologies enable single-cell and spatial transcriptomic/proteomic analyses.
- Increased gene/protein data necessitates advanced pathway-network integration strategies.
- Exploring shared and distinct biological mechanisms across datasets is crucial.
Purpose of the Study:
- To present Molecular Biology of the Cell (MBC) Pathway Networks (PathNet) for integrating and visualizing pathway data.
- To facilitate quick exploration of functional relationships between pathways.
- To provide a tool for analyzing complex biological datasets.
Main Methods:
- MBC PathNet integrates pathway information from gene and protein lists.
- Utilizes the Molecular Biology of the Cell Ontology and other ontologies.
- Visualizes pathways as interactive networks with pie charts representing datasets.
Main Results:
- PathNet enables visualization of functionally related pathways.
- Pie charts represent dataset contributions, with size indicating quantitative measures.
- Supports hierarchical and functional pathway relationships.
- Generates bar diagrams, heatmaps, and timelines.
- Offers fully automated command-line execution.
Conclusions:
- MBC PathNet provides an efficient method for pathway-network integration and visualization.
- Facilitates the exploration of complex biological mechanisms across diverse datasets.
- Supports automated analysis for large-scale biological data.
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