Clinical and Translational Bioinformatics
Our main research aims at understanding the molecular basis of hereditary disease, integrating two complementary aspects: the molecular impact of genetic variants and the regulatory role of genetic background. At a technical level, to reach our objective, we integrate the results of the most advanced genomic experiments (single-cell RNAsq, NGS sequencing, etc.) using state-of-the-art machine learning tools.
As a result of our efforts, we have recently made significant advances in understanding the functional effect of BRCA1/2 protein variants underlying hereditary breast and ovarian cancers. In fact, the methodology developed earned us the second position in the group classification at the international competition CAGI 5, held in 2019.
