PhD project research

Study, definition and implementation of innovative techniques for the analysis of medical clinical data.

Omics techniques (genomics, lipidomics, proteomics, radiomics, connectomics) generates heterogeneous, multidimensional and often redundant data that require a large amounts of space, a management in terms of models and technological approaches that are scalable and efficient. The innovative approaches of analysis are based on integration according to one holistic perspective of all data and on the analysis of the same with innovative algorithms and methodologies. The integration of the same, also using distributed and cloud architectures, in archives (such as advanced health files), allows you to build the sub-layer of data necessary for building personalized medicine applications and of accuracy (P4 medicines). This approach, recently also applied to patients affected by SARS-CoV-2, also finds numerous applications in different contexts clinicians for the development of appropriate therapies in the field of cardiovascular diseases, neurological diseases and diseases aging related. The proposed research program consists in the study and definition of advanced, distributed, high-performance, data integration, based architectures on advanced mathematical models such as knowledge graphs and multilevel networks. The result main part of this project will be the definition and prototyping of this infrastructure, even using existing elastic or cloud architectures. The feedback in terms of application provides for the application in the field of pathologies chronic such as neurodegenerative and cardiological. This project on the one hand goes to corroborate biomedical research within the healthcare system, providing for a close collaboration with the clinical part. In parallel the software tools produced they can then be prototyped and then developed in collaboration with companies in order to improve the growth effects of the local productive fabric.