Scientific Responsible for the Department: Alberto Roverato, Head of the Local Unit

Funder: Funded by the European Union- Next Generation EU

Objectives: This project concerns the development of novel principled statistical tools for the analysis of complex networks under non-standard experimental setups. The methodological innovations that can be achieved with this proposal are as follows: 1) Development of multiple, paired, and covariate-dependent graphical models for heterogeneous networks for both continuous and discrete variables, 2) Development of single and multiple graphical models for causal inference based on observational and interventional data, 3) Development of graphical models for non-normal (continuous but not Gaussian or circular data) and censored random variables. The proposed research is expected to provide a methodological foundation for novel types and classes of graphical models. Compared to existing approaches, the additional benefits of our approaches include their interpretability (such as similarity measures between groups for both graph structures and edge values), their ability to assimilate information from several dimensions and to borrow strength only between related groups and/or units, to include prior information such as known biological regulatory mechanisms, and to provide interpretable measures of uncertainty both for single network structures and similarities between groups.

Research Network:

• University of Padova
• University of Florence
• University of Palermo
• University of Milano Cattolica

Duration: October 2023 – October 2025