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CIDID Seminar: Caroline Colijn

  • Fred Hutch, Pelton Auditorium 1100 Fairview Avenue North Seattle, WA, 98109 United States (map)

Predicting strain interactions and success with genomic data: approaches from modelling and machine learning

SPEAKER: Caroline Colijn

Professor and Canada 150 Research Chair
Department of Mathematics
Simon Fraser University

ABSTRACT: Genomic data gathered over time give the opportunity to examine diversity at high resolution, and to use the results to test predictive models: can we guess in advance which sub-populations of a circulating pathogen will succeed in the near future? We discuss two contrasting approaches, one based on machine learning and the other using a high-dimensional mechanistic model that empirically captures features of the genomic data. We illustrate these approaches using data from human influenza A, Staphylococcus aureus and Streptococcus pneumoniae.

Earlier Event: September 5
CIDID Seminar: Fabio Zanini
Later Event: January 16
CIDID Seminar: Kanta Subbarao