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DTSTAMP:20260924T075447Z
DESCRIPTION:Thierry Chekouo\, PhD\n\nPostdoctoral Fellow\, Department of Bi
 ostatistics\, The University of Texas\, MD Anderson Cancer Center\n\nA Bay
 esian approach for the integrative analysis of omics data: A kidney cancer
  case study\n\nALL ARE WELCOME\n\nAbstract:\n\nIntegration of genomic data
  from multiple platforms has the capability to increase precision\, accura
 cy\, and statistical power in the identification of prognostic biomarkers.
  A fundamental problem faced in many multi-platform studies is unbalanced 
 sample sizes due to the inability to obtain measurements from all the plat
 forms for all the patients in the study. We have developed a novel Bayesia
 n approach that integrates multi-regression models to identify a small set
  of biomarkers that can accurately predict time-to-event outcomes. This me
 thod fully exploits the amount of available information across platforms a
 nd does not exclude any of the subjects from the analysis. Moreover\, inte
 ractions between platforms can be incorporated through prior distributions
  to inform the selection of biomarkers and additionally improve biomarker 
 selection accuracy. Through simulations\, we demonstrate the utility of ou
 r method and compare its performance to that of methods that do not borrow
  information across regression models. Motivated by The Cancer Genome Atla
 s kidney renal cell carcinoma dataset\, our methodology provides novel ins
 ights missed by non-integrative models.\n\nBio:\n\nDr Thierry Chekouo is c
 urrently a postdoctoral fellow at The University of Texas MD Anderson canc
 er center under the mentorship of Dr Kim-Anh Do and Dr Francesco Stingo.  
 He obtained a PhD in Statistics in 2012 at the University of Montreal unde
 r the supervision of Dr. Alejandro Murua. He also obtained a Master's degr
 ee in Mathematics in 2004 at the University of Yaounde I (Cameroon) and a 
 Master's degree in Statistics and Economics in 2007 at the Upper National 
 School of Statistics and Applied Economics in Abidjan\, Cote d'Ivoire.  Hi
 s research interests are in developing new statistical frameworks for anal
 yzing datasets characterized by high dimensionality and complex structures
  such as high-throughput genomic\, proteomic and imaging data.\n
DTSTART:20151117T203000Z
DTEND:20151117T213000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Special Seminar
URL:https://www.mcgill.ca/epi-biostat-occh/channels/event/special-seminar-2
 56278
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