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UID:20260728T232904EDT-7270AEJupT@132.216.98.100
DTSTAMP:20260729T032904Z
DESCRIPTION:Sanjeena Dang\, PhD\n\nAssistant Professor\, Department of Math
 ematics and Statistics\, University of Guelph\n\nNew developments in model
 -based clustering and applications to biological data\n\nALL ARE WELCOME\n
 \nAbstract:\n\nWith advances in high throughput technologies\, massive amo
 unts of data can be generated in an increasingly shorter period of time. C
 hallenges and approaches to dealing with high-dimensional data will be dis
 cussed in a model-based clustering context. The talk will provide an overv
 iew of different frameworks for clustering increasingly complex biological
  data using both mixtures of Gaussian distributions and mixtures of non-Ga
 ussian distributions. A number of families of mixture models will be consi
 dered along with several parameter estimation techniques and principles in
 cluding the EM algorithm\, the MM algorithm\, and the variational Bayes al
 gorithm. The talk will conclude with a discussion of future trends.\n\nBio
 :\n\nDr. Dang is Assistant Professor at the Department of Mathematics and 
 Statistics at the University of Guelph. She completed her Ph.D. in Statist
 ics at the University of Guelph in 2012 and received her masters in Statis
 tics from University of Guelph in 2009. She did her undergraduate in Biolo
 gical Sciences with courses and research focusing on Molecular Biology\, G
 enetics\, and Statistics at the University of Guelph in 2008.  Dr. Dang’s 
 current research focuses on clustering and classification of high dimensio
 nal data with applications in bioinformatics\, specifically RNA-seq data\,
  microbiome data\, and microarray data. Her research is currently supporte
 d by NSERC Discovery Grant and University of Guelph start-up research supp
 ort. Her Ph.D. research was supported through a Post Graduate Scholarship 
 (PGS-D) from the Natural Sciences and Engineering Council of Canada.\n\nFo
 r more info:  www.sanjeena.com\n
DTSTART:20151027T193000Z
DTEND:20151027T203000Z
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
 56177
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