Pepper: cytoscape app for protein complex expansion using protein-protein interaction networks

Area of Science:

• Computational Biology
• Bioinformatics
• Systems Biology

Background:

• Protein complexes are fundamental to cellular processes.
• Identifying protein complexes from proteomic data remains a challenge.
• Existing methods for protein complex discovery have limitations.

Purpose of the Study:

• To introduce Pepper, a Cytoscape application for identifying protein complexes.
• To develop a method that integrates coverage and density for robust complex identification.
• To provide a user-friendly tool for analyzing protein lists from proteomic studies.

Main Methods:

• Pepper utilizes multi-objective optimization to identify densely connected subnetworks.
• The optimization balances coverage (including seed proteins) and density (protein connectivity).
• It employs a proteome-wide interaction network and an automated post-processing pipeline.

Main Results:

• Pepper successfully identifies protein complexes as subnetworks.
• Comparative analyses on yeast and human datasets demonstrate Pepper's superiority over standard methods.
• The tool facilitates visualization and interpretation through topological analysis and data integration.

Conclusions:

• Pepper is an effective and user-friendly tool for protein complex identification.
• Its integrative approach and optimization strategy enhance the discovery of protein complexes.
• The app aids in analyzing proteomic data and understanding cellular mechanisms.