N2-0078

While knowledge discovery and data mining systems exist for mining tabular data, they generally fail to provide effective support for data analysis from the growing amounts of human-annotated semantic resources in the form of domain ontologies. The analysis of semantically annotated data is particularly challenging in biomedical domain. The project will develop scalable methods for semantic data mining enabling informative explanations of biomedical phenomena in the context of growing amounts of biomedical data, and will apply the developed methods to real-life biomedical problems. The project’s main innovation is the SDM-Open framework, fusing the scalability of network analysis methods with the explanatory potential and richness of semantic data mining algorithms, together with a novel methodology and platform, allowing researchers to tap into the growing amount of semantically annotated biomedical data, to address much broader and richer sets of research questions than now possible. The methodology will be applied to biomedical data sets, including data on Alzheimer’s disease and Parkinson’s disease.