BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference

Area of Science:

• Bioinformatics
• Computational Biology
• Systems Biology

Background:

• Protein-protein interactions (PPIs) are fundamental to cellular functions.
• High-throughput experiments have expanded PPI databases, but interactome coverage remains incomplete.
• Predicting PPIs using orthologous gene interactions (interologs) can complement experimental data.

Purpose of the Study:

• To introduce the BIANA Interolog Prediction Server (BIPS), a web-based tool for predicting PPIs.
• To leverage the BIANA framework for integrating multiple PPI databases.
• To enhance the reliability of predicted PPIs using additional metadata.

Main Methods:

• Utilized interolog information for PPI prediction.
• Integrated multiple PPI databases within the BIANA framework.
• Performed leave-one-out cross-validation to assess server performance.

Main Results:

• BIPS provides a user-friendly web interface for interolog-based PPI prediction.
• The server integrates diverse PPI data sources.
• Calculated specificity ranged from 72% to 98%, while sensitivity varied from 1% to 59% based on sequence identity cut-offs.

Conclusions:

• BIPS facilitates the prediction of protein-protein interactions using interolog information.
• The server enhances the identification of potential PPIs, contributing to more complete interactome maps.
• BIPS is freely available, supporting biological research and network analysis.