Whole-Graph Embedding and Adversarial Attacks for Life Sciences

Networks provide a suitable model for many scientific and technological problems that require the representation of complex entities and their relations. Life sciences applications include systems biology, where molecular components are represented in integrated systems in which the interactions among them provide richer information than single components taken separately, or neuroimaging, where brain networks allow representing the connectivity between different brain locations. In the examples we focus on, a set of networks is available, with each network representing an entity (e.g., a molecule, a macro molecule, or a patient) and links expressing their relation in the chemical/biological domain.