Systems Biology

We integrate high-dimensional omics data from multiple sources to build computational frameworks enabling a systems-level investigation of the molecular mechanisms underlying disease phenotypes, patient heterogeneity and therapeutic response. We investigate how genetics, transcriptomics and proteomics profiles can reveal pathways, nominate causal genes, identify biomarkers and characterize cell identities to guide drug repurposing, also using network-based approaches to map relationships among key molecular players. Our computational strategies support complex data analysis and candidate prioritization, enabling robust, evidence-based translational decision-making.