The fibrotic process is a major factor in the development of many chronic diseases such as liver cirrhosis, pulmonary fibrosis, and cardiac fibrosis. Understanding the molecular and cellular pathways that regulate fibrosis is crucial for the discovery of new relevant biomarkers and the development of targeted therapies aimed at preventing or reversing this detrimental process.
The Data Science group strives R&D projects in the field of computational proteomics to master efficiently the successive steps from MS data acquisition and management to meaningful result production and biological knowledge extraction.
Thanks to specific actions on the biochemical, theanalytical and the data processing fronts. we have made a number of advances in the precise, high-throughput and large-scale characterization of proteomes.
Our research aims to dissect how the functional specificities of histone sequence variants and diverse lysine acylation motifs intersect, to shape chromatin structure and transcriptional outcomes.
Through developments in nanoresonator design, signal processing optimization, and the integration of novel particle introduction schemes, NEMS-MS is establishing itself as a complementary method to conventional techniques for the characterization of nanoparticles, intact biomolecules, and viruses.
This activity aims to develop robust proteomics pipelines for the phenotyping of patients through in-depth characterization of biofluid proteomes, the identification of new biomarkers and the improved comprehension of pathogenetic mechanisms.