Biomolecules Folding and Disease

email: emidio.capriotti@unibo.it        emidio.capriotti@biofold.org Phone: +39 051 209 4303 Fax: +39 051 209 4286

         I am principal investigator of the BioFolD Group. Since 2019, I am associate professor of the Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Italy. In November 2024, I was also appointed as Joint Faculty in the Computational Genomics Platform at the IRCCS University Hospital of Bologna, where I contribute to translating computational methods into genomics applications for rare diseases.

         My academic career spans several institutions. From July 2015 to September 2016, I served as junior group leader at the Institute of Mathematical Modeling of Biological Systems, University of Düsseldorf, Germany. From 2012 to 2015, I was assistant professor in the Department of Pathology at the University of Alabama at Birmingham (UAB), USA. Prior to that, I was a Marie Curie International Outgoing Fellow in the Bioengineering Department at Stanford University. My postdoctoral training includes two years in the Biocomputing Group at the University of Bologna and three years in the Structural Bioinformatics Unit at the CIPF in Valencia, Spain.

         I hold a PhD in Physical Sciences from the University of Bologna. My scientific background is in Structural Bioinformatics, and over the last decade my research has focused on understanding the functional impact of Single Nucleotide Variants (SNVs) that cause single amino acid changes. I have developed machine learning methods to predict the effect of point mutations on protein stability, including tools for estimating the free energy change associated with nsSNVs. More recently, my research has expanded to investigate the relationship between SNVs and the onset of human disease. By integrating information from protein sequences, evolutionary profiles, and functional annotations, I have developed several widely used web server tools for predicting disease-related protein mutations.

         The main goal of my research is to unravel the complex relationship between genomic variation and disease by leveraging large-scale data from high-throughput technologies. I am particularly interested in designing disease-specific algorithms and computational tools that advance personal genomics and precision medicine. For further details on my scientific activity and publications, please refer to my full CV.