The unit develops and applies computational approaches that integrate experimental data with knowledge extracted from the biomedical literature.

Protein–Protein Interaction Discovery

Using the UniReD platform, the unit identifies potential functional associations between proteins based on evidence extracted from the biomedical literature and clustering of related proteins.

This approach enables the discovery of functional network relationships beyond curated protein interaction databases.

Biomarker Prioritization and Candidate Molecule Discovery

The multiUniReD platform prioritizes potential biomarkers using scoring systems applied to protein clusters derived from large-scale experimental datasets.

This approach supports the identification and evaluation of candidate molecules associated with specific phenotypes.

Biomedical Literature Mining

The unit also develops literature mining methodologies through the BioTextQuest platform.

The system enables the identification of important biomedical concepts, including:

• Genes
• Proteins
• Diseases
• Biological processes

thereby facilitating hypothesis generation and literature-guided interpretation of omics datasets.

Systems Biology

The research team develops computational approaches for the analysis and visualization of biological networks.

Current research activities include:

• Construction and analysis of protein–protein interaction (PPI) networks
• Network-based interpretation of omics datasets
• Visualization of protein–disease interaction networks
• Integrated analyses combining transcriptomics, proteomics, and knowledge-based interaction networks

These approaches support systems-level investigation of the molecular mechanisms underlying complex diseases.