MBC PathNet

MBC PathNet integrates and visualizes networks of functionally related pathways predicted from transcriptomic and proteomic datasets using the Molecular Biology of the Cell Ontology and other ontologies to facilitate exploration of shared and distinct mechanisms across datasets.

Key Features:

• Network Visualization: Pathways are visualized as pie charts within networks of hierarchical parent-child relationships or functional relationships, where each slice represents a dataset that predicted that pathway.
• Customizable Pie Chart Sizing: Sizes of pies and slices can be selected to represent statistical significance or other quantitative measures.
• Additional Plot Types: MBC PathNet can generate bar diagrams, heatmaps, and timelines.
• Command Line Execution: Fully automated execution from the command line is supported.

Scientific Applications:

• Multi-Dataset Pathway Integration: Integration of networks of functionally related pathways predicted from gene and protein lists across multiple transcriptomic and proteomic datasets.
• Cross-Dataset Mechanism Comparison: Exploration of shared and distinct mechanisms across transcriptomic and proteomic datasets through pathway-network based integration strategies.

Methodology:

MBC PathNet predicts networks of functionally related pathways from gene and protein lists using the Molecular Biology of the Cell Ontology and other ontologies, with pathways connected through hierarchical parent-child relationships or functional relationships.