My Background
I hold a bachelor's and a master's degree in Life Sciences Engineering from EPFL. During my master, I specialized in computational biology, cultivating the ability to comprehend and dissect intricate biological datasets. My master's thesis focused on investigating the role of alternative polyadenylation in resistance to BRAF inhibitors in the context of melanoma therapy. To do so, I developed a bioinformatic pipeline tailored for the analysis of alternative polyadenylation in single-cell RNA sequencing data. To further continue my research within the GHI group, I embarked on a PhD journey in August 2023, enrolling in the Computational and Quantitative Biology doctoral school at EPFL.
My Research Interests
Driven by a profound fascination with the intricate complexities and inherent organization of the human body, I am enthusiastic about crafting computational methodologies to analyze vast biological datasets, with the goal of extracting statistically significant and interpretable signals. My specific focus lies in unraveling the role of non-coding regions within mRNA, and especially of 3' UTRs, in the context of cancer research. Beyond the molecular scale, I am equally intrigued by the spatial orchestration of these mechanisms at both cellular and tissue levels.
My Publications
1. R Luisier, C Andreassi, L Fournier, A Riccio. The predicted RNA-binding protein regulome of axonal mRNAs. Genome Research (2023).