disease disease relationships

Presented a methodology (and related algorithms) to automatically induce a hierarchical structure from proximity relations between disease modules. We compared the interactome-induced disease taxonomy with a human-curated disease taxonomy.

Proposed a novel machine learning methodology to shed light on disease similarities by analyzing the relationship between categorical proximity of diseases in human-curated ontologies and structural proximity of their disease module in the human interactome.

Developed a methodology and related algorithms to automatically induce a hierarchical structure of disease modules from proximity relations in the interactome network, and to align, label, and systematically compare this structure with a manually defined disease ontology.