Research:
PhD student in Bioinformatics and Computational Biology with a background in biological sciences and a focus on NGS data analysis, single-cell RNA sequencing (scRNA-seq), and bioinformatics pipeline optimization. My academic journey has been shaped by a genuine interest in integrating biology and computational approaches to contribute to advancements in diagnostics and precision medicine.
During my Master’s degree studies and thesis, I worked on transcriptomic data analysis in breast cancer, studying molecular pathways involved in disease progression. This experience allowed me to build my programming skills in Python and R, and to gain valuable experience with bioinformatics tools and workflows. I further built on these skills during an internship at a Next-Generation Sequencing (NGS) facility, where I had the opportunity to work on sequencing workflows, from raw data acquisition to genomic and transcriptomic analyses. Exposure to technologies such as RNA-seq and scRNA-seq encouraged me to further explore the potential of computational biology in healthcare and diagnostics.
Throughout my studies, I have also developed an interest in omics approaches, including genomics, proteomics and metabolomics, which continue to guide my research. I am particularly interested in contributing to the development of bioinformatics pipelines that connect biological research with clinical applications, aiming to support progress in precision medicine and innovative therapies.