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DTSTAMP:20251120T095804Z
DESCRIPTION:Magali Richard\, PhD\n\nCNRS Research Associate\n	Université Gre
 noble Alpes\n	\n	NOTE: Meet & Greet Prof Magali Richard from 3-3:30pm in Roo
 m 1140\n\nWHEN: Wednesday\, October 29\, 2025\, from 3:30 to 4:30 p.m.\n	WH
 ERE: Hybrid | 2001 ɬÀï·¬ College Avenue\, Rm 1140\; Zoom\n	NOTE: Magali Ri
 chard will be presenting in-person at SPGH\n	 \n\nAbstract\n\nCancer is a h
 ighly heterogeneous disease\, where tumors evolve as multicellular ecosyst
 ems shaped by dynamic interactions among diverse cell types. This heteroge
 neity drives cancer progression but remains difficult to quantify and inte
 rpret\, limiting our understanding of its role in oncogenesis. At the inte
 rsection of bioinformatics\, biostatistics\, and oncology\, our work devel
 ops computational approaches to analyze high-dimensional\, multimodal mole
 cular data. In this talk\, I will present two examples of our methodologic
 al advances. First\, a novel statistical framework based on mixture models
  to infer cellular heterogeneity from DNA methylation rates. Second\, a hi
 gh-dimensional mediation analysis showing how DNA methylation and immune i
 nfiltration mediate the effect of tobacco exposure on pancreatic adenocarc
 inoma outcomes. Beyond these contributions\, I will also discuss our effor
 ts to promote collaborative benchmarking and evaluation of computational a
 lgorithms through data challenge frameworks\, with the goal of building ro
 bust and reproducible tools for the cancer research community.\n\n\n	Speake
 r Bio\n\nI am a researcher in bioinformatics and the Computer Science Labo
 ratory of Grenoble (France). I have with a background in molecular biology
 \, genetics\, and computational biology. My research focuses on tumor hete
 rogeneity\, method development\, and cancer biology\, and I also promote c
 ollaborative science by organizing data challenges.\n	\n	Website: https://ma
 grichard.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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