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Hi, I’m Veronica!

My curiosity for the mechanisms underlying human diseases led me to start a Bachelor Degree in Biomedical Laboratory techniques (Unimi, Milan), which offered me the opportunity to do a two-years internship at the Metabolic Diseases Research Lab (Policlinico Hospital, Milan), where I acquired hands-on experience on molecular biology and CRISPR-cas9 gene editing working side-by-side with passionate scientists. There, I came across the challenges the analysis of biological data encompasses and I realized how important interdisciplinarity is for research.

So, I decided to do a Master’s in Bioinformatics for Computational Genomics (Politecnico of Milan) to learn to implement computational strategies for the analysis of a broad range of data. For my thesis internship, I spent more than a year at the European Institute of Oncology (IEO, Milan) working on a pipeline for the analysis of Oxford Nanopore long reads from Acute Myeloid Leukemia cells at the bulk and single-cell level.

Today, I’m ecstatic to be part of the ENHPATHY team. I consider this innovative program an invaluable chance for me to learn new skills to apply to my research while getting in touch with some of the best professionals in this field and other passionate young researchers.

Besides research, I love cooking traditional Italian recipes.

My research project

Computational approaches to discover noncoding mutations underlying human disease (WP3)

Human genetics is rapidly moving from the analysis of protein-coding sequences to whole genome sequences. Our ability to discern non-protein coding mutations that cause disease from a vast excess of non-functional mutations is still limited. This PhD project will focus on an ERC-funded large-scale enhancer mutation screen in patients with monogenic diabetes. It will develop computational approaches to inform on the pathogenicity and function of enhancer mutations, using data from ongoing experimental and patient screens.

Applicants with diverse educational backgrounds are welcome, but a computing background is important, including basic knowledge of a programming language (e.g Python, R). Expertise in statistical analysis is also highly relevant.


My publications