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From RNA to histological images: linking the transcriptome with human phenotypes through statistical learning

Author
Muñoz, M.
Type of activity
Theses
Other related units
Department of Statistics and Operations Research
Defense's date
2021-04-07
URL
http://hdl.handle.net/2117/348916 Open in new window
Abstract
Genomic datasets are fundamental to broaden our understanding of human biology in the context of health and disease. However, the high-dimensional nature of gene expression and other molecular traits poses a challenge when attempting to find associations of these data types with human phenotypes. To this end, this thesis relies on statistical learning tools to mitigate the curse of dimensionality and link the human transcriptome with phenotypes at different orders of complexity: from RNA, to com...
Group of research
COSDA-UPC - COmpositional and Spatial Data Analysis

Participants

  • Muñoz Aguirre, Manuel  (author)
  • Radeva, Petia  (secretary)
  • Valencia Herrera, Alfonso  (president)
  • Graffelman, Jan  (director)

Attachments