PhD Course: Constructing Knowledge Graphs for Advanced Biomedical Applications

Knowledge graphs (KGs) can be used as an integration means of heterogenous biomedical concepts and relationships existing in different biological data sources. The presence of various 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 this course, we will discuss 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 to construct and analyze knowledge graphs in different biomedical applications. Finally, we will discuss techniques and examples for the construction of biological knowledge graphs.