Research interests
Our main research aims at understanding the molecular basis of hereditary disease, integrating two complementary aspects: the molecular impact of causative variants and how genetic background regulates the propagation of this impact. At a technical level, to reach our objective, we integrate the results of the most advanced genomic experiments (single-cell, Hi-C, etc.) using state-of-the-art machine learning tools. To enhance the biomedical reach of our research, we work in collaboration with clinical groups from different hospitals. As a result of these efforts, we have recently made significant advances in understanding the functional effect of BRCA1/2 protein variants underlying hereditary breast and ovarian cancers. Finally, mention that we are also devoting an important part of our efforts to the fundamental study of epigenetic processes, to reach a full picture of which phenomena contribute to the generation of phenotype and, more precisely, of clinical phenotype.
Selected publications
Selected research activities
- Jan 2024: Delivered the talk ‘When the Future is Now: The Rising Contribution of AI to the Clinical Understanding of Genetic Variability’ at the XI International Conference BIFI 2024, Zaragoza, Spain.
- Jun 2024: Co-organizer ‘Jornada sobre l’ús de la IA en Recerca Biomèdica’ at Vall d’Hebron Hospital, Barcelona, Spain.
- Oct 2024: Taught a 10-hour degree course on Machine Learning for Pathogenicity Prediction at the University of Bologna, Italy.
- Oct 2024: Participated in the ‘Back to Fundamentals of Research: Interdisciplinarity Roundtable’ at ISA, Bologna, Italy, with the talk ‘Pathogenicity Prediction Using AI Tools.’
- Dec 2024: Organized a visit for Biomedicine degree students from the Universitat Internacional de Catalunya (UIC) to our laboratory to share our research on AI/ML applications in pathogenicity prediction