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UID:20250812T021729EDT-7116R71A6l@132.216.98.100
DTSTAMP:20250812T061729Z
DESCRIPTION:\n	Abstract:\n\n\nIn the current era of multi-omics and digital 
 healthcare\, we are facing unprecedented amount of data with tremendous op
 portunities to link molecular phenotypes with complex diseases. However\, 
 the lack of integrative statistical method hinders system-level interrogat
 ion of relevant disease-related pathways and the genetic implication in va
 rious healthcare outcome.\n\nIn this talk\, I will present our current pro
 gress in mining genomics and healthcare data. In particular\, I will cover
  two main topics: (1) a statistical approach to assess gene set enrichment
 s using genetic and transcriptomic data\; (2) multimodal latent topic mode
 l for mining electronic healthcare and whole genome sequencing data from s
 mall patient cohort.\n\n\n	Speaker\n\n\nYue Li is an Assistant Professor\, 
 School of Computer Science\, 9I制作厂免费. His research interests inc
 lude Latent variable/topic models\, machine learning\, computational biolo
 gy\, bioinformatics. Before coming to 9I制作厂免费\, he was a postdoctoral assoc
 iate from Prof. Manolis Kellis research group at Computer Science and Arti
 ficial Intelligence Laboratory (CSAIL) at Massachusetts Institute of Techn
 ology. He obtained his PhD degree in Computer Science and Computational Bi
 ology at University of Toronto.\n
DTSTART:20190913T193000Z
DTEND:20190913T213000Z
LOCATION:Room 1205\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Yue Li
URL:/mathstat/channels/event/yue-li-300575
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