Magali Richard (CNRS, University Grenoble-Alpes)
鉁掞笍 TITLE / TITRE
Statistical and computational methods for the analysis of tumor heterogeneity
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馃搫 ABSTRACT /听R脡SUM脡
Cancer is a highly heterogeneous disease, where tumors evolve as multicellular ecosystems shaped by dynamic interactions among diverse cell types. This heterogeneity drives cancer progression but remains difficult to quantify and interpret, limiting our understanding of its role in oncogenesis. At the intersection of bioinformatics, biostatistics, and oncology, our work develops computational approaches to analyze high-dimensional, multimodal molecular data. In this talk, I will present two examples of our methodological advances.
First, a novel statistical framework based on mixture models to infer cellular heterogeneity from DNA methylation rates.
Second, a high-dimensional mediation analysis showing how DNA methylation and immune infiltration mediate the effect of tobacco exposure on pancreatic adenocarcinoma outcomes.
Beyond these contributions, I will also discuss our efforts to promote collaborative benchmarking and evaluation of computational algorithms through data challenge frameworks, with the goal of building robust and reproducible tools for the cancer research community.
馃搷 PLACE / LIEU
Hybride - CRM, Salle / Room 5340, Pavillon Andr茅 Aisenstadt
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