The current research conducted at DM comprises three groups:
Computational Bodily Fluids and Cardiac Modelling:
The computational bodily fluids group focuses on modeling applied to the quantitative description of the movement of bodily fluids and their interaction with blood vessels and other tissues. The main areas of research are twofold: (i) the construction of highly detailed computational models for studying fundamental questions regarding the physiology and pathology of the cardiovascular system and related systems, and (ii) the study of specific clinical problems that arise in hospital settings (in collaboration with DICAM and DISI). Currently, we collaborate with three local hospitals (S. Maria del Carmine Hospital in Rovereto, Santa Chiara Hospital in Trento, and Civil Hospital in Arco) on various projects, as well as with St. Olav University Hospital (Trondheim, Norway). These models require the discretization of partial and ordinary differential equations in one or more spatial dimensions with complex geometries, as well as the integration of patient-specific data.
For many years, there has been ongoing research on epidemic spread models in humans and other animals, in close collaboration with FBK, FEM, and numerous universities and research centers. Through mathematical models, we have analyzed seasonal influenza epidemics, as well as the 2009 influenza pandemic, studying the effects of control strategies ranging from social distancing interventions to the preventive use of antiviral drugs and vaccination. Another research topic has been vector-borne infections (particularly mosquitoes), analyzing the potential for the spread of tropical diseases such as dengue or chikungunya depending on the timing and location of a case’s entry into Italy, and studying the factors that contribute most to the increase in human cases of West Nile virus. The pandemic caused by the SARS-CoV2 virus has demonstrated the potential of mathematical modeling to infer key epidemic parameters from partial and “noisy” data and to provide scenario analyses following possible interventions.
Biomedical Statistics and Data Science:
The research objectives of Biomedical Statistics and Data Science focus on studying complex biological systems based on omics data, which increasingly characterize scientific research in the biomedical field. Omics data are molecular profiles of various types (RNA profiles, protein profiles, methylation profiles, genetic profiles), and their study has revolutionized biological research by allowing simultaneous reading of all elements of a class of molecules (RNA, proteins, etc.) present in a biological system at a certain moment. The Data Analysis group's research focuses on new methods of interpreting this data to address problems such as drug resistance in certain types of tumors (in collaboration with a group from the Human Technopole), the mechanisms underlying neurodegenerative diseases (collaboration with the University of Bologna, CIBIO, and Aptuit), the identification of molecular biomarkers for diagnostic and prognostic use (collaboration with GSK Vaccines), and the metabolic alterations related to the interaction between diet and an individual's genotype (collaboration with Nestle Institute of Health Sciences). Many of these projects have also been carried out in collaboration with researchers from the COSBI Institute, which provides opportunities for numerous collaborations, especially in the pharmaceutical and academic fields.