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UID:20251027T195409EDT-0837ZUlkwZ@132.216.98.100
DTSTAMP:20251027T235409Z
DESCRIPTION:Magali Richard\, PhD\n\nCNRS Research Associate\n	Université Gre
 noble Alpes\n	\n	NOTE: Meet & Greet Magali Richard from 3-3:30pm in Room 114
 0\n\nWHEN: Wednesday\, October 29\, 2025\, from 3:30 to 4:30 p.m.\n	WHERE: 
 Hybrid | 2001 ºÚÁÏÍø College Avenue\, Rm 1140\; Zoom\n	NOTE: Magali Richard
  will be presenting in-person at SPGH\n	 \n\nAbstract\n\nCancer is a highly
  heterogeneous disease\, where tumors evolve as multicellular ecosystems s
 haped 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 intersect
 ion of bioinformatics\, biostatistics\, and oncology\, our work develops c
 omputational approaches to analyze high-dimensional\, multimodal molecular
  data. In this talk\, I will present two examples of our methodological ad
 vances. First\, a novel statistical framework based on mixture models to i
 nfer cellular heterogeneity from DNA methylation rates. Second\, a high-di
 mensional mediation analysis showing how DNA methylation and immune infilt
 ration 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 algori
 thms through data challenge frameworks\, with the goal of building robust 
 and reproducible tools for the cancer research community.\n\n\n	Speaker Bio
 \n\nI am a researcher in bioinformatics and the Computer Science Laborator
 y of Grenoble (France). I have with a background in molecular biology\, ge
 netics\, and computational biology. My research focuses on tumor heterogen
 eity\, method development\, and cancer biology\, and I also promote collab
 orative science by organizing data challenges.\n	\n	Website: https://magrich
 ard.github.io/\n
DTSTART:20251029T193000Z
DTEND:20251029T203000Z
SUMMARY:Statistical and Computational Methods for the Analysis of Tumor Het
 erogeneity
URL:/epi-biostat-occh/channels/event/statistical-and-c
 omputational-methods-analysis-tumor-heterogeneity-368360
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