Path2enet: generation of human pathway-derived networks in an expression specific context

Area of Science:

• Bioinformatics
• Systems Biology
• Molecular Biology

Background:

• Biological pathways are complex cellular wiring diagrams.
• Visualizing these pathways aids understanding but can be simplified.
• Bioinformatics offers computational approaches to network analysis.

Purpose of the Study:

• To develop a bioinformatics tool for translating biological pathways into protein networks.
• To integrate pathway data with gene expression and protein interaction data.
• To provide a computer-based, multiplex view of cellular processes.

Main Methods:

• Developed Path2enet, an R package.
• Integrated data from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.
• Incorporated gene expression and protein-protein interaction data.
• Utilized expression data to identify active (ON) or inactive (OFF) proteins.

Main Results:

• Path2enet translates biological pathways into active protein networks.
• The tool reduces network complexity, highlighting expressed proteins under specific conditions.
• Demonstrated utility by generating NOTCH Signaling Pathway networks for human B and T lymphocytes using microarray data.

Conclusions:

• Path2enet is an open-source tool for constructing pathway-expression-networks.
• It integrates biological pathways, protein interactions, and cell-specific gene expression data.
• Aims to provide a more integrative, global view of protein interactions in cellular systems.