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Personalized medicine

A Graphical Modeling Framework to Study Complex Dependence Patterns in High-Dimensional Biological Data

Project Leader(s): 

[url=mailto:[email protected]]Dr. Laurent Briollais[/url] , University of Toronto

Project Website: 

http://research.lunenfeld.ca/mprime_Briollais/DEFAULT.ASP

Project team: 
Dr. Gary Bader, University of Toronto
Dr. Adrian Dobra, University of Washington
Dr. Hélène Massam, York University
Dr. Hilmi Ozcelik, Samuel Lunenfeld Research Institute
Non-academic participants: 

[url=http://www.genizon.com/]Genizon Biosciences Inc.[/url]

[url=http://www.wolfram.com/]Wolfram Research[/url]

[url=http://www.ibm.com/ca/en/]IBM[/url]

[url=http://www.tgen.org/]Translational Genomics Research Institute[/url]

Funding period: 
1 April 2021 - 31 March 2021

Graphical models have been one of the most efficient statistical tools used in the last twenty years for the analysis of complex structured high-dimensional data. Graphical models provide a probabilistic framework for making inference and representing the knowledge that we have about these complex structured data. In biological research and more particularly in the emerging -omics disciplines such as genomics, proteomics, metabolomics, transcriptomics, data are often generated from complex high throughput experiments and from complex experimental designs.

Tags: 
health