Multi-omics data integration for explainability analysis to improve clinical biomarkers identification.
Francesca Cordero, University of Torino
Wednesday, June 7th 2023; 4:00pm-5:00pm

Abstract: The availability of deep sequencing technologies is rapidly increasing and specifically, their usage become useful to identify novel molecular biomarkers of human pathological phenotypes. However, the computational approaches to integrate omics data remain far to be easily used in clinical settings. In this presentation, an overview of the main approaches and some solutions to functional data integration will be presented.

Bio: Francesca Cordero is a computational biologist working at the intersection of computer science, molecular biology, and medical science to develop methodologies to answer research questions and novel ways to analyze and interpret data. She graduated in molecular biology from the University of Turin and subsequently undertook her Ph.D. in computer science in Turin. Her research interests in computational biology were developed during her Ph.D. training at Washington University where she investigated transcriptional factor detection using probabilistic graphical models. She returned to Turin and started to work as Researcher in 2012. Her research focuses on understanding cancer progression in terms of cellular and molecular mechanisms in order to define clinically-relevant biomarkers through computational analysis and models. In her work, her strengths have been in being able to understand both sides: the medical and the computational. This gives her the opportunity to understand the requests of the medical and biological side and find the optimal solution for them.