BioPlexR and BioPlexPy: integrated data products for the analysis of human protein interactions

Area of Science:

• Proteomics
• Systems Biology
• Bioinformatics

Background:

• The BioPlex project has generated large-scale protein-protein interaction (PPI) networks.
• Understanding cellular processes requires comprehensive interaction data.

Purpose of the Study:

• To describe programmatic access to BioPlex PPI networks and integrated biological resources.
• To facilitate downstream analysis of PPI data using R and Python.

Main Methods:

• Development of R and Python packages for accessing BioPlex data.
• Integration of PPI networks with CORUM complex data, PFAM domains, PDB structures, and transcriptomic/proteomic data.
• Implementation of functions for network analysis, domain-domain association, and structure mapping.

Main Results:

• Creation of two cell-line-specific PPI networks (293T and HCT116) with extensive interactions and proteins.
• Availability of programmatic access to these networks and associated datasets.
• Development of tools for integrative analysis, including sub-network analysis and PPI mapping onto structures.

Conclusions:

• The BioPlex R and Python packages offer a robust platform for analyzing large-scale PPI data.
• These resources support integrative studies combining PPIs with other omics data.
• The tools enable advanced analyses like maximum scoring sub-network identification and structural mapping of interactions.