The initiative joins forces from AI, clinical and life-sciences experts working on the analysis of complex and multi-sourced biomedical data integrating clinical evidence on COVID-19 with genomic and proteomic information, as well as molecular data. We are exploring data-driven AI methodologies and bioinformatics approaches covering network data analysis, machine learning, and deep learning for graphs, predictive modelling, and feature selection of Omics data. Prof. G. Stilo and Dr. L. Madeddu et. al. assembled a resource that fuses information from heterogeneous sources and different studies from the literature into a unique network-based representation, facilitating the use of relational and graph-based learning methods. Dataset on Github
CLAIRE - Confederation of Laboratories for Artificial Intelligence Research in Europe