The research team focuses on developing methods for processing and organising large bases of heterogeneous biomedical data and related metadata, such as clinical phoniatric EEG/ERP records, audio/video records, CT and MRI images, within their entire life-cycle. The research activities include analyses of input data and related metadata, their semantic description, long-term storage, sharing and efficient retrieval on a semantic level, considering protection requirements. It may involve, e.g., automated or semi-automated segmentation of medical images, followed by a 3D extraction of surface or volumetric networks or organs. The database serves as a foundation in simulation models for in-silico research of biological systems’ behaviour under given conditions, e.g. muscle deformation resulting from bone movements. Calculation tools are developed to make clinical diagnostics more accurate (e.g. timely diagnostics of the serious larynx and inner ear diseases, osteoporotic diseases diagnostics, diagnostics based on a set of symptoms) and to predict the development of a disease in time (e.g. prediction of glucose concentrations in blood in next 15 minutes for an insulin pump, the probable outcome based on the known disease history of other patients).