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.
Whole-Graph Embedding and Adversarial Attacks for Life Sciences
Maddalena L;Giordano M;Guarracino;
2022
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
