Length: 20 hours - 4 cfu
Abstract:
Knowledge graphs can be used as an integration means of heterogenous biomedical concepts and relationships existing in different biological data sources. The presence of heterogeneous information related to the same topic (e.g. patients, therapies, diseases) can be exploited for tackling many biomedical problems, such as finding new treatments for existing drugs, aiding efforts to diagnose patients, and identifying associations between diseases and biomolecules. In the course, we will provide background notions on the characteristics of knowledge graphs, the languages for their representation and querying, and the systems used for their storage. Then, we will discuss machine learning techniques that can be used for the construction and mining of knowledge graphs in different kinds of biomedical applications.
Dates & Venue
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Lecturer:
Prof. Marco Mesiti - Dipartimento di Informatica
Assessor:
Prof. Marco Mesiti - Dipartimento di Informatica